Wxxxx commited on
Commit
c83515c
·
verified ·
1 Parent(s): b522cfb

Upload folder using huggingface_hub

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. .gitattributes +4 -0
  2. Direction/Ageis_Danger/README.md +208 -0
  3. Direction/Ageis_Danger/adapter_config.json +42 -0
  4. Direction/Ageis_Danger/adapter_model.safetensors +3 -0
  5. Direction/Ageis_Danger/added_tokens.json +28 -0
  6. Direction/Ageis_Danger/chat_template.jinja +89 -0
  7. Direction/Ageis_Danger/merges.txt +0 -0
  8. Direction/Ageis_Danger/special_tokens_map.json +31 -0
  9. Direction/Ageis_Danger/tokenizer.json +3 -0
  10. Direction/Ageis_Danger/tokenizer_config.json +240 -0
  11. Direction/Ageis_Danger/trainer_state.json +2659 -0
  12. Direction/Ageis_Danger/training_args.bin +3 -0
  13. Direction/Ageis_Danger/vocab.json +0 -0
  14. Direction/Beaver-Danger/README.md +208 -0
  15. Direction/Beaver-Danger/adapter_config.json +42 -0
  16. Direction/Beaver-Danger/adapter_model.safetensors +3 -0
  17. Direction/Beaver-Danger/added_tokens.json +28 -0
  18. Direction/Beaver-Danger/chat_template.jinja +89 -0
  19. Direction/Beaver-Danger/merges.txt +0 -0
  20. Direction/Beaver-Danger/special_tokens_map.json +31 -0
  21. Direction/Beaver-Danger/tokenizer.json +3 -0
  22. Direction/Beaver-Danger/tokenizer_config.json +240 -0
  23. Direction/Beaver-Danger/trainer_state.json +2659 -0
  24. Direction/Beaver-Danger/training_args.bin +3 -0
  25. Direction/Beaver-Danger/vocab.json +0 -0
  26. Direction/PKURLHF-10K_Safety/README.md +202 -0
  27. Direction/PKURLHF-10K_Safety/adapter_config.json +39 -0
  28. Direction/PKURLHF-10K_Safety/adapter_model.safetensors +3 -0
  29. Direction/PKURLHF-10K_Safety/added_tokens.json +28 -0
  30. Direction/PKURLHF-10K_Safety/chat_template.jinja +89 -0
  31. Direction/PKURLHF-10K_Safety/merges.txt +0 -0
  32. Direction/PKURLHF-10K_Safety/optimizer.pt +3 -0
  33. Direction/PKURLHF-10K_Safety/rng_state.pth +3 -0
  34. Direction/PKURLHF-10K_Safety/scheduler.pt +3 -0
  35. Direction/PKURLHF-10K_Safety/special_tokens_map.json +31 -0
  36. Direction/PKURLHF-10K_Safety/tokenizer.json +3 -0
  37. Direction/PKURLHF-10K_Safety/tokenizer_config.json +240 -0
  38. Direction/PKURLHF-10K_Safety/trainer_state.json +0 -0
  39. Direction/PKURLHF-10K_Safety/training_args.bin +3 -0
  40. Direction/PKURLHF-10K_Safety/vocab.json +0 -0
  41. README.md +46 -3
  42. initial-state/dolly_ckpt_5850/README.md +202 -0
  43. initial-state/dolly_ckpt_5850/adapter_config.json +39 -0
  44. initial-state/dolly_ckpt_5850/adapter_model.safetensors +3 -0
  45. initial-state/dolly_ckpt_5850/added_tokens.json +28 -0
  46. initial-state/dolly_ckpt_5850/chat_template.jinja +89 -0
  47. initial-state/dolly_ckpt_5850/merges.txt +0 -0
  48. initial-state/dolly_ckpt_5850/optimizer.pt +3 -0
  49. initial-state/dolly_ckpt_5850/rng_state.pth +3 -0
  50. initial-state/dolly_ckpt_5850/scheduler.pt +3 -0
.gitattributes CHANGED
@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ Direction/Ageis_Danger/tokenizer.json filter=lfs diff=lfs merge=lfs -text
37
+ Direction/Beaver-Danger/tokenizer.json filter=lfs diff=lfs merge=lfs -text
38
+ Direction/PKURLHF-10K_Safety/tokenizer.json filter=lfs diff=lfs merge=lfs -text
39
+ initial-state/dolly_ckpt_5850/tokenizer.json filter=lfs diff=lfs merge=lfs -text
Direction/Ageis_Danger/README.md ADDED
@@ -0,0 +1,208 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Qwen/Qwen3-8B
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:/workspace/jzc/model/Qwen3-8B
7
+ - llama-factory
8
+ - lora
9
+ - transformers
10
+ ---
11
+
12
+ # Model Card for Model ID
13
+
14
+ <!-- Provide a quick summary of what the model is/does. -->
15
+
16
+
17
+
18
+ ## Model Details
19
+
20
+ ### Model Description
21
+
22
+ <!-- Provide a longer summary of what this model is. -->
23
+
24
+
25
+
26
+ - **Developed by:** [More Information Needed]
27
+ - **Funded by [optional]:** [More Information Needed]
28
+ - **Shared by [optional]:** [More Information Needed]
29
+ - **Model type:** [More Information Needed]
30
+ - **Language(s) (NLP):** [More Information Needed]
31
+ - **License:** [More Information Needed]
32
+ - **Finetuned from model [optional]:** [More Information Needed]
33
+
34
+ ### Model Sources [optional]
35
+
36
+ <!-- Provide the basic links for the model. -->
37
+
38
+ - **Repository:** [More Information Needed]
39
+ - **Paper [optional]:** [More Information Needed]
40
+ - **Demo [optional]:** [More Information Needed]
41
+
42
+ ## Uses
43
+
44
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
45
+
46
+ ### Direct Use
47
+
48
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Downstream Use [optional]
53
+
54
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
55
+
56
+ [More Information Needed]
57
+
58
+ ### Out-of-Scope Use
59
+
60
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ## Bias, Risks, and Limitations
65
+
66
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
67
+
68
+ [More Information Needed]
69
+
70
+ ### Recommendations
71
+
72
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
73
+
74
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
75
+
76
+ ## How to Get Started with the Model
77
+
78
+ Use the code below to get started with the model.
79
+
80
+ [More Information Needed]
81
+
82
+ ## Training Details
83
+
84
+ ### Training Data
85
+
86
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
87
+
88
+ [More Information Needed]
89
+
90
+ ### Training Procedure
91
+
92
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
93
+
94
+ #### Preprocessing [optional]
95
+
96
+ [More Information Needed]
97
+
98
+
99
+ #### Training Hyperparameters
100
+
101
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
102
+
103
+ #### Speeds, Sizes, Times [optional]
104
+
105
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
106
+
107
+ [More Information Needed]
108
+
109
+ ## Evaluation
110
+
111
+ <!-- This section describes the evaluation protocols and provides the results. -->
112
+
113
+ ### Testing Data, Factors & Metrics
114
+
115
+ #### Testing Data
116
+
117
+ <!-- This should link to a Dataset Card if possible. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Factors
122
+
123
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
124
+
125
+ [More Information Needed]
126
+
127
+ #### Metrics
128
+
129
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
130
+
131
+ [More Information Needed]
132
+
133
+ ### Results
134
+
135
+ [More Information Needed]
136
+
137
+ #### Summary
138
+
139
+
140
+
141
+ ## Model Examination [optional]
142
+
143
+ <!-- Relevant interpretability work for the model goes here -->
144
+
145
+ [More Information Needed]
146
+
147
+ ## Environmental Impact
148
+
149
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
150
+
151
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
152
+
153
+ - **Hardware Type:** [More Information Needed]
154
+ - **Hours used:** [More Information Needed]
155
+ - **Cloud Provider:** [More Information Needed]
156
+ - **Compute Region:** [More Information Needed]
157
+ - **Carbon Emitted:** [More Information Needed]
158
+
159
+ ## Technical Specifications [optional]
160
+
161
+ ### Model Architecture and Objective
162
+
163
+ [More Information Needed]
164
+
165
+ ### Compute Infrastructure
166
+
167
+ [More Information Needed]
168
+
169
+ #### Hardware
170
+
171
+ [More Information Needed]
172
+
173
+ #### Software
174
+
175
+ [More Information Needed]
176
+
177
+ ## Citation [optional]
178
+
179
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
180
+
181
+ **BibTeX:**
182
+
183
+ [More Information Needed]
184
+
185
+ **APA:**
186
+
187
+ [More Information Needed]
188
+
189
+ ## Glossary [optional]
190
+
191
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
192
+
193
+ [More Information Needed]
194
+
195
+ ## More Information [optional]
196
+
197
+ [More Information Needed]
198
+
199
+ ## Model Card Authors [optional]
200
+
201
+ [More Information Needed]
202
+
203
+ ## Model Card Contact
204
+
205
+ [More Information Needed]
206
+ ### Framework versions
207
+
208
+ - PEFT 0.17.1
Direction/Ageis_Danger/adapter_config.json ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/jzc/model/Qwen3-8B",
5
+ "bias": "none",
6
+ "corda_config": null,
7
+ "eva_config": null,
8
+ "exclude_modules": null,
9
+ "fan_in_fan_out": false,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 16,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0.0,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "qalora_group_size": 16,
24
+ "r": 8,
25
+ "rank_pattern": {},
26
+ "revision": null,
27
+ "target_modules": [
28
+ "down_proj",
29
+ "q_proj",
30
+ "gate_proj",
31
+ "v_proj",
32
+ "o_proj",
33
+ "up_proj",
34
+ "k_proj"
35
+ ],
36
+ "target_parameters": null,
37
+ "task_type": "CAUSAL_LM",
38
+ "trainable_token_indices": null,
39
+ "use_dora": false,
40
+ "use_qalora": false,
41
+ "use_rslora": false
42
+ }
Direction/Ageis_Danger/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6264a511500b07de2227578730dd4701a9b3a53cf51032eb0aec99594ca44751
3
+ size 87360584
Direction/Ageis_Danger/added_tokens.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</think>": 151668,
3
+ "</tool_call>": 151658,
4
+ "</tool_response>": 151666,
5
+ "<think>": 151667,
6
+ "<tool_call>": 151657,
7
+ "<tool_response>": 151665,
8
+ "<|box_end|>": 151649,
9
+ "<|box_start|>": 151648,
10
+ "<|endoftext|>": 151643,
11
+ "<|file_sep|>": 151664,
12
+ "<|fim_middle|>": 151660,
13
+ "<|fim_pad|>": 151662,
14
+ "<|fim_prefix|>": 151659,
15
+ "<|fim_suffix|>": 151661,
16
+ "<|im_end|>": 151645,
17
+ "<|im_start|>": 151644,
18
+ "<|image_pad|>": 151655,
19
+ "<|object_ref_end|>": 151647,
20
+ "<|object_ref_start|>": 151646,
21
+ "<|quad_end|>": 151651,
22
+ "<|quad_start|>": 151650,
23
+ "<|repo_name|>": 151663,
24
+ "<|video_pad|>": 151656,
25
+ "<|vision_end|>": 151653,
26
+ "<|vision_pad|>": 151654,
27
+ "<|vision_start|>": 151652
28
+ }
Direction/Ageis_Danger/chat_template.jinja ADDED
@@ -0,0 +1,89 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0].role == 'system' %}
4
+ {{- messages[0].content + '\n\n' }}
5
+ {%- endif %}
6
+ {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
7
+ {%- for tool in tools %}
8
+ {{- "\n" }}
9
+ {{- tool | tojson }}
10
+ {%- endfor %}
11
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
12
+ {%- else %}
13
+ {%- if messages[0].role == 'system' %}
14
+ {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
15
+ {%- endif %}
16
+ {%- endif %}
17
+ {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
18
+ {%- for message in messages[::-1] %}
19
+ {%- set index = (messages|length - 1) - loop.index0 %}
20
+ {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
21
+ {%- set ns.multi_step_tool = false %}
22
+ {%- set ns.last_query_index = index %}
23
+ {%- endif %}
24
+ {%- endfor %}
25
+ {%- for message in messages %}
26
+ {%- if message.content is string %}
27
+ {%- set content = message.content %}
28
+ {%- else %}
29
+ {%- set content = '' %}
30
+ {%- endif %}
31
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
32
+ {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
33
+ {%- elif message.role == "assistant" %}
34
+ {%- set reasoning_content = '' %}
35
+ {%- if message.reasoning_content is string %}
36
+ {%- set reasoning_content = message.reasoning_content %}
37
+ {%- else %}
38
+ {%- if '</think>' in content %}
39
+ {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
40
+ {%- set content = content.split('</think>')[-1].lstrip('\n') %}
41
+ {%- endif %}
42
+ {%- endif %}
43
+ {%- if loop.index0 > ns.last_query_index %}
44
+ {%- if loop.last or (not loop.last and reasoning_content) %}
45
+ {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
46
+ {%- else %}
47
+ {{- '<|im_start|>' + message.role + '\n' + content }}
48
+ {%- endif %}
49
+ {%- else %}
50
+ {{- '<|im_start|>' + message.role + '\n' + content }}
51
+ {%- endif %}
52
+ {%- if message.tool_calls %}
53
+ {%- for tool_call in message.tool_calls %}
54
+ {%- if (loop.first and content) or (not loop.first) %}
55
+ {{- '\n' }}
56
+ {%- endif %}
57
+ {%- if tool_call.function %}
58
+ {%- set tool_call = tool_call.function %}
59
+ {%- endif %}
60
+ {{- '<tool_call>\n{"name": "' }}
61
+ {{- tool_call.name }}
62
+ {{- '", "arguments": ' }}
63
+ {%- if tool_call.arguments is string %}
64
+ {{- tool_call.arguments }}
65
+ {%- else %}
66
+ {{- tool_call.arguments | tojson }}
67
+ {%- endif %}
68
+ {{- '}\n</tool_call>' }}
69
+ {%- endfor %}
70
+ {%- endif %}
71
+ {{- '<|im_end|>\n' }}
72
+ {%- elif message.role == "tool" %}
73
+ {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
74
+ {{- '<|im_start|>user' }}
75
+ {%- endif %}
76
+ {{- '\n<tool_response>\n' }}
77
+ {{- content }}
78
+ {{- '\n</tool_response>' }}
79
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
80
+ {{- '<|im_end|>\n' }}
81
+ {%- endif %}
82
+ {%- endif %}
83
+ {%- endfor %}
84
+ {%- if add_generation_prompt %}
85
+ {{- '<|im_start|>assistant\n' }}
86
+ {%- if enable_thinking is defined and enable_thinking is false %}
87
+ {{- '<think>\n\n</think>\n\n' }}
88
+ {%- endif %}
89
+ {%- endif %}
Direction/Ageis_Danger/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
Direction/Ageis_Danger/special_tokens_map.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>",
5
+ "<|object_ref_start|>",
6
+ "<|object_ref_end|>",
7
+ "<|box_start|>",
8
+ "<|box_end|>",
9
+ "<|quad_start|>",
10
+ "<|quad_end|>",
11
+ "<|vision_start|>",
12
+ "<|vision_end|>",
13
+ "<|vision_pad|>",
14
+ "<|image_pad|>",
15
+ "<|video_pad|>"
16
+ ],
17
+ "eos_token": {
18
+ "content": "<|im_end|>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ },
24
+ "pad_token": {
25
+ "content": "<|endoftext|>",
26
+ "lstrip": false,
27
+ "normalized": false,
28
+ "rstrip": false,
29
+ "single_word": false
30
+ }
31
+ }
Direction/Ageis_Danger/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
3
+ size 11422654
Direction/Ageis_Danger/tokenizer_config.json ADDED
@@ -0,0 +1,240 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "151643": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "151644": {
14
+ "content": "<|im_start|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "151645": {
22
+ "content": "<|im_end|>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "151646": {
30
+ "content": "<|object_ref_start|>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "151647": {
38
+ "content": "<|object_ref_end|>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "151648": {
46
+ "content": "<|box_start|>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ },
53
+ "151649": {
54
+ "content": "<|box_end|>",
55
+ "lstrip": false,
56
+ "normalized": false,
57
+ "rstrip": false,
58
+ "single_word": false,
59
+ "special": true
60
+ },
61
+ "151650": {
62
+ "content": "<|quad_start|>",
63
+ "lstrip": false,
64
+ "normalized": false,
65
+ "rstrip": false,
66
+ "single_word": false,
67
+ "special": true
68
+ },
69
+ "151651": {
70
+ "content": "<|quad_end|>",
71
+ "lstrip": false,
72
+ "normalized": false,
73
+ "rstrip": false,
74
+ "single_word": false,
75
+ "special": true
76
+ },
77
+ "151652": {
78
+ "content": "<|vision_start|>",
79
+ "lstrip": false,
80
+ "normalized": false,
81
+ "rstrip": false,
82
+ "single_word": false,
83
+ "special": true
84
+ },
85
+ "151653": {
86
+ "content": "<|vision_end|>",
87
+ "lstrip": false,
88
+ "normalized": false,
89
+ "rstrip": false,
90
+ "single_word": false,
91
+ "special": true
92
+ },
93
+ "151654": {
94
+ "content": "<|vision_pad|>",
95
+ "lstrip": false,
96
+ "normalized": false,
97
+ "rstrip": false,
98
+ "single_word": false,
99
+ "special": true
100
+ },
101
+ "151655": {
102
+ "content": "<|image_pad|>",
103
+ "lstrip": false,
104
+ "normalized": false,
105
+ "rstrip": false,
106
+ "single_word": false,
107
+ "special": true
108
+ },
109
+ "151656": {
110
+ "content": "<|video_pad|>",
111
+ "lstrip": false,
112
+ "normalized": false,
113
+ "rstrip": false,
114
+ "single_word": false,
115
+ "special": true
116
+ },
117
+ "151657": {
118
+ "content": "<tool_call>",
119
+ "lstrip": false,
120
+ "normalized": false,
121
+ "rstrip": false,
122
+ "single_word": false,
123
+ "special": false
124
+ },
125
+ "151658": {
126
+ "content": "</tool_call>",
127
+ "lstrip": false,
128
+ "normalized": false,
129
+ "rstrip": false,
130
+ "single_word": false,
131
+ "special": false
132
+ },
133
+ "151659": {
134
+ "content": "<|fim_prefix|>",
135
+ "lstrip": false,
136
+ "normalized": false,
137
+ "rstrip": false,
138
+ "single_word": false,
139
+ "special": false
140
+ },
141
+ "151660": {
142
+ "content": "<|fim_middle|>",
143
+ "lstrip": false,
144
+ "normalized": false,
145
+ "rstrip": false,
146
+ "single_word": false,
147
+ "special": false
148
+ },
149
+ "151661": {
150
+ "content": "<|fim_suffix|>",
151
+ "lstrip": false,
152
+ "normalized": false,
153
+ "rstrip": false,
154
+ "single_word": false,
155
+ "special": false
156
+ },
157
+ "151662": {
158
+ "content": "<|fim_pad|>",
159
+ "lstrip": false,
160
+ "normalized": false,
161
+ "rstrip": false,
162
+ "single_word": false,
163
+ "special": false
164
+ },
165
+ "151663": {
166
+ "content": "<|repo_name|>",
167
+ "lstrip": false,
168
+ "normalized": false,
169
+ "rstrip": false,
170
+ "single_word": false,
171
+ "special": false
172
+ },
173
+ "151664": {
174
+ "content": "<|file_sep|>",
175
+ "lstrip": false,
176
+ "normalized": false,
177
+ "rstrip": false,
178
+ "single_word": false,
179
+ "special": false
180
+ },
181
+ "151665": {
182
+ "content": "<tool_response>",
183
+ "lstrip": false,
184
+ "normalized": false,
185
+ "rstrip": false,
186
+ "single_word": false,
187
+ "special": false
188
+ },
189
+ "151666": {
190
+ "content": "</tool_response>",
191
+ "lstrip": false,
192
+ "normalized": false,
193
+ "rstrip": false,
194
+ "single_word": false,
195
+ "special": false
196
+ },
197
+ "151667": {
198
+ "content": "<think>",
199
+ "lstrip": false,
200
+ "normalized": false,
201
+ "rstrip": false,
202
+ "single_word": false,
203
+ "special": false
204
+ },
205
+ "151668": {
206
+ "content": "</think>",
207
+ "lstrip": false,
208
+ "normalized": false,
209
+ "rstrip": false,
210
+ "single_word": false,
211
+ "special": false
212
+ }
213
+ },
214
+ "additional_special_tokens": [
215
+ "<|im_start|>",
216
+ "<|im_end|>",
217
+ "<|object_ref_start|>",
218
+ "<|object_ref_end|>",
219
+ "<|box_start|>",
220
+ "<|box_end|>",
221
+ "<|quad_start|>",
222
+ "<|quad_end|>",
223
+ "<|vision_start|>",
224
+ "<|vision_end|>",
225
+ "<|vision_pad|>",
226
+ "<|image_pad|>",
227
+ "<|video_pad|>"
228
+ ],
229
+ "bos_token": null,
230
+ "clean_up_tokenization_spaces": false,
231
+ "eos_token": "<|im_end|>",
232
+ "errors": "replace",
233
+ "extra_special_tokens": {},
234
+ "model_max_length": 131072,
235
+ "pad_token": "<|endoftext|>",
236
+ "padding_side": "right",
237
+ "split_special_tokens": false,
238
+ "tokenizer_class": "Qwen2Tokenizer",
239
+ "unk_token": null
240
+ }
Direction/Ageis_Danger/trainer_state.json ADDED
@@ -0,0 +1,2659 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 10.0,
6
+ "eval_steps": 500,
7
+ "global_step": 3750,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.02666666666666667,
14
+ "grad_norm": 0.6864556074142456,
15
+ "learning_rate": 1.2000000000000002e-07,
16
+ "loss": 2.0431,
17
+ "step": 10
18
+ },
19
+ {
20
+ "epoch": 0.05333333333333334,
21
+ "grad_norm": 0.6834467649459839,
22
+ "learning_rate": 2.533333333333333e-07,
23
+ "loss": 2.0222,
24
+ "step": 20
25
+ },
26
+ {
27
+ "epoch": 0.08,
28
+ "grad_norm": 0.7390895485877991,
29
+ "learning_rate": 3.8666666666666674e-07,
30
+ "loss": 2.0474,
31
+ "step": 30
32
+ },
33
+ {
34
+ "epoch": 0.10666666666666667,
35
+ "grad_norm": 0.8008406758308411,
36
+ "learning_rate": 5.2e-07,
37
+ "loss": 2.087,
38
+ "step": 40
39
+ },
40
+ {
41
+ "epoch": 0.13333333333333333,
42
+ "grad_norm": 0.7216496467590332,
43
+ "learning_rate": 6.533333333333334e-07,
44
+ "loss": 2.0767,
45
+ "step": 50
46
+ },
47
+ {
48
+ "epoch": 0.16,
49
+ "grad_norm": 0.7768703699111938,
50
+ "learning_rate": 7.866666666666667e-07,
51
+ "loss": 2.0302,
52
+ "step": 60
53
+ },
54
+ {
55
+ "epoch": 0.18666666666666668,
56
+ "grad_norm": 0.9261518120765686,
57
+ "learning_rate": 9.200000000000001e-07,
58
+ "loss": 2.0068,
59
+ "step": 70
60
+ },
61
+ {
62
+ "epoch": 0.21333333333333335,
63
+ "grad_norm": 0.6796293258666992,
64
+ "learning_rate": 1.0533333333333333e-06,
65
+ "loss": 2.0384,
66
+ "step": 80
67
+ },
68
+ {
69
+ "epoch": 0.24,
70
+ "grad_norm": 1.0748271942138672,
71
+ "learning_rate": 1.1866666666666668e-06,
72
+ "loss": 2.104,
73
+ "step": 90
74
+ },
75
+ {
76
+ "epoch": 0.26666666666666666,
77
+ "grad_norm": 0.9115467667579651,
78
+ "learning_rate": 1.32e-06,
79
+ "loss": 2.0462,
80
+ "step": 100
81
+ },
82
+ {
83
+ "epoch": 0.29333333333333333,
84
+ "grad_norm": 0.915414035320282,
85
+ "learning_rate": 1.4533333333333335e-06,
86
+ "loss": 2.0701,
87
+ "step": 110
88
+ },
89
+ {
90
+ "epoch": 0.32,
91
+ "grad_norm": 1.0734838247299194,
92
+ "learning_rate": 1.586666666666667e-06,
93
+ "loss": 2.066,
94
+ "step": 120
95
+ },
96
+ {
97
+ "epoch": 0.3466666666666667,
98
+ "grad_norm": 1.0868602991104126,
99
+ "learning_rate": 1.72e-06,
100
+ "loss": 2.0059,
101
+ "step": 130
102
+ },
103
+ {
104
+ "epoch": 0.37333333333333335,
105
+ "grad_norm": 1.1686838865280151,
106
+ "learning_rate": 1.8533333333333333e-06,
107
+ "loss": 2.0448,
108
+ "step": 140
109
+ },
110
+ {
111
+ "epoch": 0.4,
112
+ "grad_norm": 1.0780514478683472,
113
+ "learning_rate": 1.9866666666666666e-06,
114
+ "loss": 1.9928,
115
+ "step": 150
116
+ },
117
+ {
118
+ "epoch": 0.4266666666666667,
119
+ "grad_norm": 1.1489983797073364,
120
+ "learning_rate": 2.12e-06,
121
+ "loss": 2.0029,
122
+ "step": 160
123
+ },
124
+ {
125
+ "epoch": 0.4533333333333333,
126
+ "grad_norm": 1.2736639976501465,
127
+ "learning_rate": 2.2533333333333335e-06,
128
+ "loss": 1.9858,
129
+ "step": 170
130
+ },
131
+ {
132
+ "epoch": 0.48,
133
+ "grad_norm": 1.3319426774978638,
134
+ "learning_rate": 2.386666666666667e-06,
135
+ "loss": 1.9551,
136
+ "step": 180
137
+ },
138
+ {
139
+ "epoch": 0.5066666666666667,
140
+ "grad_norm": 1.349578619003296,
141
+ "learning_rate": 2.52e-06,
142
+ "loss": 1.872,
143
+ "step": 190
144
+ },
145
+ {
146
+ "epoch": 0.5333333333333333,
147
+ "grad_norm": 0.9017946720123291,
148
+ "learning_rate": 2.6533333333333335e-06,
149
+ "loss": 1.8316,
150
+ "step": 200
151
+ },
152
+ {
153
+ "epoch": 0.56,
154
+ "grad_norm": 1.002862811088562,
155
+ "learning_rate": 2.786666666666667e-06,
156
+ "loss": 1.8138,
157
+ "step": 210
158
+ },
159
+ {
160
+ "epoch": 0.5866666666666667,
161
+ "grad_norm": 0.8344107866287231,
162
+ "learning_rate": 2.92e-06,
163
+ "loss": 1.7294,
164
+ "step": 220
165
+ },
166
+ {
167
+ "epoch": 0.6133333333333333,
168
+ "grad_norm": 0.9120360016822815,
169
+ "learning_rate": 3.053333333333334e-06,
170
+ "loss": 1.7006,
171
+ "step": 230
172
+ },
173
+ {
174
+ "epoch": 0.64,
175
+ "grad_norm": 0.883114218711853,
176
+ "learning_rate": 3.186666666666667e-06,
177
+ "loss": 1.6236,
178
+ "step": 240
179
+ },
180
+ {
181
+ "epoch": 0.6666666666666666,
182
+ "grad_norm": 0.8164843916893005,
183
+ "learning_rate": 3.3200000000000004e-06,
184
+ "loss": 1.6641,
185
+ "step": 250
186
+ },
187
+ {
188
+ "epoch": 0.6933333333333334,
189
+ "grad_norm": 0.8954416513442993,
190
+ "learning_rate": 3.4533333333333334e-06,
191
+ "loss": 1.6328,
192
+ "step": 260
193
+ },
194
+ {
195
+ "epoch": 0.72,
196
+ "grad_norm": 0.8396301865577698,
197
+ "learning_rate": 3.5866666666666673e-06,
198
+ "loss": 1.6047,
199
+ "step": 270
200
+ },
201
+ {
202
+ "epoch": 0.7466666666666667,
203
+ "grad_norm": 0.9113221168518066,
204
+ "learning_rate": 3.7200000000000004e-06,
205
+ "loss": 1.6098,
206
+ "step": 280
207
+ },
208
+ {
209
+ "epoch": 0.7733333333333333,
210
+ "grad_norm": 0.7408691048622131,
211
+ "learning_rate": 3.853333333333334e-06,
212
+ "loss": 1.5339,
213
+ "step": 290
214
+ },
215
+ {
216
+ "epoch": 0.8,
217
+ "grad_norm": 0.9837501645088196,
218
+ "learning_rate": 3.986666666666667e-06,
219
+ "loss": 1.592,
220
+ "step": 300
221
+ },
222
+ {
223
+ "epoch": 0.8266666666666667,
224
+ "grad_norm": 0.9414945840835571,
225
+ "learning_rate": 4.12e-06,
226
+ "loss": 1.5275,
227
+ "step": 310
228
+ },
229
+ {
230
+ "epoch": 0.8533333333333334,
231
+ "grad_norm": 0.6915170550346375,
232
+ "learning_rate": 4.253333333333334e-06,
233
+ "loss": 1.4722,
234
+ "step": 320
235
+ },
236
+ {
237
+ "epoch": 0.88,
238
+ "grad_norm": 1.0188401937484741,
239
+ "learning_rate": 4.3866666666666665e-06,
240
+ "loss": 1.4897,
241
+ "step": 330
242
+ },
243
+ {
244
+ "epoch": 0.9066666666666666,
245
+ "grad_norm": 0.7740457057952881,
246
+ "learning_rate": 4.520000000000001e-06,
247
+ "loss": 1.377,
248
+ "step": 340
249
+ },
250
+ {
251
+ "epoch": 0.9333333333333333,
252
+ "grad_norm": 0.6730086207389832,
253
+ "learning_rate": 4.653333333333333e-06,
254
+ "loss": 1.392,
255
+ "step": 350
256
+ },
257
+ {
258
+ "epoch": 0.96,
259
+ "grad_norm": 0.855743944644928,
260
+ "learning_rate": 4.786666666666667e-06,
261
+ "loss": 1.3936,
262
+ "step": 360
263
+ },
264
+ {
265
+ "epoch": 0.9866666666666667,
266
+ "grad_norm": 0.718235969543457,
267
+ "learning_rate": 4.92e-06,
268
+ "loss": 1.3313,
269
+ "step": 370
270
+ },
271
+ {
272
+ "epoch": 1.0133333333333334,
273
+ "grad_norm": 0.6589620113372803,
274
+ "learning_rate": 4.999982670673473e-06,
275
+ "loss": 1.3231,
276
+ "step": 380
277
+ },
278
+ {
279
+ "epoch": 1.04,
280
+ "grad_norm": 0.7204256653785706,
281
+ "learning_rate": 4.999787718509086e-06,
282
+ "loss": 1.312,
283
+ "step": 390
284
+ },
285
+ {
286
+ "epoch": 1.0666666666666667,
287
+ "grad_norm": 0.7311373949050903,
288
+ "learning_rate": 4.999376169470306e-06,
289
+ "loss": 1.3119,
290
+ "step": 400
291
+ },
292
+ {
293
+ "epoch": 1.0933333333333333,
294
+ "grad_norm": 0.6310704946517944,
295
+ "learning_rate": 4.998748059216254e-06,
296
+ "loss": 1.2798,
297
+ "step": 410
298
+ },
299
+ {
300
+ "epoch": 1.12,
301
+ "grad_norm": 0.7810817360877991,
302
+ "learning_rate": 4.997903442170241e-06,
303
+ "loss": 1.2968,
304
+ "step": 420
305
+ },
306
+ {
307
+ "epoch": 1.1466666666666667,
308
+ "grad_norm": 0.7063048481941223,
309
+ "learning_rate": 4.996842391515045e-06,
310
+ "loss": 1.277,
311
+ "step": 430
312
+ },
313
+ {
314
+ "epoch": 1.1733333333333333,
315
+ "grad_norm": 0.6194319725036621,
316
+ "learning_rate": 4.995564999186572e-06,
317
+ "loss": 1.3146,
318
+ "step": 440
319
+ },
320
+ {
321
+ "epoch": 1.2,
322
+ "grad_norm": 0.8911550045013428,
323
+ "learning_rate": 4.994071375865898e-06,
324
+ "loss": 1.2271,
325
+ "step": 450
326
+ },
327
+ {
328
+ "epoch": 1.2266666666666666,
329
+ "grad_norm": 0.7139999866485596,
330
+ "learning_rate": 4.992361650969668e-06,
331
+ "loss": 1.2009,
332
+ "step": 460
333
+ },
334
+ {
335
+ "epoch": 1.2533333333333334,
336
+ "grad_norm": 0.7921785712242126,
337
+ "learning_rate": 4.990435972638888e-06,
338
+ "loss": 1.241,
339
+ "step": 470
340
+ },
341
+ {
342
+ "epoch": 1.28,
343
+ "grad_norm": 0.6499159336090088,
344
+ "learning_rate": 4.988294507726089e-06,
345
+ "loss": 1.2606,
346
+ "step": 480
347
+ },
348
+ {
349
+ "epoch": 1.3066666666666666,
350
+ "grad_norm": 0.8065305352210999,
351
+ "learning_rate": 4.98593744178087e-06,
352
+ "loss": 1.2408,
353
+ "step": 490
354
+ },
355
+ {
356
+ "epoch": 1.3333333333333333,
357
+ "grad_norm": 0.603751003742218,
358
+ "learning_rate": 4.983364979033819e-06,
359
+ "loss": 1.1539,
360
+ "step": 500
361
+ },
362
+ {
363
+ "epoch": 1.3599999999999999,
364
+ "grad_norm": 0.6962315440177917,
365
+ "learning_rate": 4.980577342378818e-06,
366
+ "loss": 1.2015,
367
+ "step": 510
368
+ },
369
+ {
370
+ "epoch": 1.3866666666666667,
371
+ "grad_norm": 0.7914028763771057,
372
+ "learning_rate": 4.977574773353732e-06,
373
+ "loss": 1.2067,
374
+ "step": 520
375
+ },
376
+ {
377
+ "epoch": 1.4133333333333333,
378
+ "grad_norm": 0.7412983775138855,
379
+ "learning_rate": 4.974357532119478e-06,
380
+ "loss": 1.1334,
381
+ "step": 530
382
+ },
383
+ {
384
+ "epoch": 1.44,
385
+ "grad_norm": 0.8885224461555481,
386
+ "learning_rate": 4.970925897437484e-06,
387
+ "loss": 1.2074,
388
+ "step": 540
389
+ },
390
+ {
391
+ "epoch": 1.4666666666666668,
392
+ "grad_norm": 0.6707415580749512,
393
+ "learning_rate": 4.967280166645538e-06,
394
+ "loss": 1.2794,
395
+ "step": 550
396
+ },
397
+ {
398
+ "epoch": 1.4933333333333334,
399
+ "grad_norm": 1.029408574104309,
400
+ "learning_rate": 4.9634206556320186e-06,
401
+ "loss": 1.1519,
402
+ "step": 560
403
+ },
404
+ {
405
+ "epoch": 1.52,
406
+ "grad_norm": 0.7895164489746094,
407
+ "learning_rate": 4.959347698808532e-06,
408
+ "loss": 1.1693,
409
+ "step": 570
410
+ },
411
+ {
412
+ "epoch": 1.5466666666666666,
413
+ "grad_norm": 0.7517342567443848,
414
+ "learning_rate": 4.95506164908093e-06,
415
+ "loss": 1.1478,
416
+ "step": 580
417
+ },
418
+ {
419
+ "epoch": 1.5733333333333333,
420
+ "grad_norm": 0.7386269569396973,
421
+ "learning_rate": 4.9505628778187365e-06,
422
+ "loss": 1.154,
423
+ "step": 590
424
+ },
425
+ {
426
+ "epoch": 1.6,
427
+ "grad_norm": 0.7774485349655151,
428
+ "learning_rate": 4.94585177482297e-06,
429
+ "loss": 1.197,
430
+ "step": 600
431
+ },
432
+ {
433
+ "epoch": 1.6266666666666667,
434
+ "grad_norm": 0.6724669337272644,
435
+ "learning_rate": 4.940928748292363e-06,
436
+ "loss": 1.1248,
437
+ "step": 610
438
+ },
439
+ {
440
+ "epoch": 1.6533333333333333,
441
+ "grad_norm": 0.8252294659614563,
442
+ "learning_rate": 4.9357942247879995e-06,
443
+ "loss": 1.1685,
444
+ "step": 620
445
+ },
446
+ {
447
+ "epoch": 1.6800000000000002,
448
+ "grad_norm": 0.8395477533340454,
449
+ "learning_rate": 4.930448649196356e-06,
450
+ "loss": 1.1423,
451
+ "step": 630
452
+ },
453
+ {
454
+ "epoch": 1.7066666666666666,
455
+ "grad_norm": 0.797327995300293,
456
+ "learning_rate": 4.924892484690744e-06,
457
+ "loss": 1.195,
458
+ "step": 640
459
+ },
460
+ {
461
+ "epoch": 1.7333333333333334,
462
+ "grad_norm": 0.8169471621513367,
463
+ "learning_rate": 4.91912621269119e-06,
464
+ "loss": 1.1516,
465
+ "step": 650
466
+ },
467
+ {
468
+ "epoch": 1.76,
469
+ "grad_norm": 0.9324586391448975,
470
+ "learning_rate": 4.913150332822716e-06,
471
+ "loss": 1.1535,
472
+ "step": 660
473
+ },
474
+ {
475
+ "epoch": 1.7866666666666666,
476
+ "grad_norm": 0.9258119463920593,
477
+ "learning_rate": 4.906965362872048e-06,
478
+ "loss": 1.14,
479
+ "step": 670
480
+ },
481
+ {
482
+ "epoch": 1.8133333333333335,
483
+ "grad_norm": 0.7775595188140869,
484
+ "learning_rate": 4.9005718387427546e-06,
485
+ "loss": 1.1633,
486
+ "step": 680
487
+ },
488
+ {
489
+ "epoch": 1.8399999999999999,
490
+ "grad_norm": 0.9818838238716125,
491
+ "learning_rate": 4.893970314408813e-06,
492
+ "loss": 1.1303,
493
+ "step": 690
494
+ },
495
+ {
496
+ "epoch": 1.8666666666666667,
497
+ "grad_norm": 0.7248987555503845,
498
+ "learning_rate": 4.887161361866608e-06,
499
+ "loss": 1.116,
500
+ "step": 700
501
+ },
502
+ {
503
+ "epoch": 1.8933333333333333,
504
+ "grad_norm": 0.7499696612358093,
505
+ "learning_rate": 4.880145571085369e-06,
506
+ "loss": 1.1252,
507
+ "step": 710
508
+ },
509
+ {
510
+ "epoch": 1.92,
511
+ "grad_norm": 0.9208846092224121,
512
+ "learning_rate": 4.872923549956058e-06,
513
+ "loss": 1.1746,
514
+ "step": 720
515
+ },
516
+ {
517
+ "epoch": 1.9466666666666668,
518
+ "grad_norm": 0.8718836903572083,
519
+ "learning_rate": 4.86549592423869e-06,
520
+ "loss": 1.1291,
521
+ "step": 730
522
+ },
523
+ {
524
+ "epoch": 1.9733333333333334,
525
+ "grad_norm": 0.8388645052909851,
526
+ "learning_rate": 4.857863337508119e-06,
527
+ "loss": 1.1033,
528
+ "step": 740
529
+ },
530
+ {
531
+ "epoch": 2.0,
532
+ "grad_norm": 0.8666885495185852,
533
+ "learning_rate": 4.850026451098271e-06,
534
+ "loss": 1.1277,
535
+ "step": 750
536
+ },
537
+ {
538
+ "epoch": 2.026666666666667,
539
+ "grad_norm": 1.0474607944488525,
540
+ "learning_rate": 4.841985944044845e-06,
541
+ "loss": 1.1568,
542
+ "step": 760
543
+ },
544
+ {
545
+ "epoch": 2.0533333333333332,
546
+ "grad_norm": 0.9431724548339844,
547
+ "learning_rate": 4.833742513026478e-06,
548
+ "loss": 1.0784,
549
+ "step": 770
550
+ },
551
+ {
552
+ "epoch": 2.08,
553
+ "grad_norm": 0.7262744307518005,
554
+ "learning_rate": 4.825296872304377e-06,
555
+ "loss": 1.1638,
556
+ "step": 780
557
+ },
558
+ {
559
+ "epoch": 2.1066666666666665,
560
+ "grad_norm": 0.9374427795410156,
561
+ "learning_rate": 4.816649753660431e-06,
562
+ "loss": 1.0557,
563
+ "step": 790
564
+ },
565
+ {
566
+ "epoch": 2.1333333333333333,
567
+ "grad_norm": 0.8942416310310364,
568
+ "learning_rate": 4.807801906333809e-06,
569
+ "loss": 1.0435,
570
+ "step": 800
571
+ },
572
+ {
573
+ "epoch": 2.16,
574
+ "grad_norm": 0.8669484257698059,
575
+ "learning_rate": 4.7987540969560385e-06,
576
+ "loss": 1.0561,
577
+ "step": 810
578
+ },
579
+ {
580
+ "epoch": 2.1866666666666665,
581
+ "grad_norm": 0.9552891850471497,
582
+ "learning_rate": 4.789507109484579e-06,
583
+ "loss": 1.1086,
584
+ "step": 820
585
+ },
586
+ {
587
+ "epoch": 2.2133333333333334,
588
+ "grad_norm": 0.9328513145446777,
589
+ "learning_rate": 4.7800617451348974e-06,
590
+ "loss": 1.1033,
591
+ "step": 830
592
+ },
593
+ {
594
+ "epoch": 2.24,
595
+ "grad_norm": 0.8567037582397461,
596
+ "learning_rate": 4.770418822311046e-06,
597
+ "loss": 1.0873,
598
+ "step": 840
599
+ },
600
+ {
601
+ "epoch": 2.2666666666666666,
602
+ "grad_norm": 0.7724719047546387,
603
+ "learning_rate": 4.760579176534747e-06,
604
+ "loss": 1.0785,
605
+ "step": 850
606
+ },
607
+ {
608
+ "epoch": 2.2933333333333334,
609
+ "grad_norm": 0.8977177143096924,
610
+ "learning_rate": 4.750543660373004e-06,
611
+ "loss": 1.0793,
612
+ "step": 860
613
+ },
614
+ {
615
+ "epoch": 2.32,
616
+ "grad_norm": 1.0932681560516357,
617
+ "learning_rate": 4.7403131433642226e-06,
618
+ "loss": 1.0835,
619
+ "step": 870
620
+ },
621
+ {
622
+ "epoch": 2.3466666666666667,
623
+ "grad_norm": 0.922770619392395,
624
+ "learning_rate": 4.729888511942877e-06,
625
+ "loss": 1.0805,
626
+ "step": 880
627
+ },
628
+ {
629
+ "epoch": 2.3733333333333335,
630
+ "grad_norm": 0.9030175805091858,
631
+ "learning_rate": 4.719270669362699e-06,
632
+ "loss": 1.0933,
633
+ "step": 890
634
+ },
635
+ {
636
+ "epoch": 2.4,
637
+ "grad_norm": 1.004112958908081,
638
+ "learning_rate": 4.708460535618411e-06,
639
+ "loss": 1.1069,
640
+ "step": 900
641
+ },
642
+ {
643
+ "epoch": 2.4266666666666667,
644
+ "grad_norm": 1.0625816583633423,
645
+ "learning_rate": 4.697459047366022e-06,
646
+ "loss": 1.0471,
647
+ "step": 910
648
+ },
649
+ {
650
+ "epoch": 2.453333333333333,
651
+ "grad_norm": 0.8528280258178711,
652
+ "learning_rate": 4.68626715784166e-06,
653
+ "loss": 1.0602,
654
+ "step": 920
655
+ },
656
+ {
657
+ "epoch": 2.48,
658
+ "grad_norm": 1.1137285232543945,
659
+ "learning_rate": 4.674885836778983e-06,
660
+ "loss": 1.089,
661
+ "step": 930
662
+ },
663
+ {
664
+ "epoch": 2.506666666666667,
665
+ "grad_norm": 1.0087735652923584,
666
+ "learning_rate": 4.6633160703251556e-06,
667
+ "loss": 1.1693,
668
+ "step": 940
669
+ },
670
+ {
671
+ "epoch": 2.533333333333333,
672
+ "grad_norm": 0.829055666923523,
673
+ "learning_rate": 4.6515588609554006e-06,
674
+ "loss": 1.0238,
675
+ "step": 950
676
+ },
677
+ {
678
+ "epoch": 2.56,
679
+ "grad_norm": 1.0512988567352295,
680
+ "learning_rate": 4.639615227386141e-06,
681
+ "loss": 1.1054,
682
+ "step": 960
683
+ },
684
+ {
685
+ "epoch": 2.586666666666667,
686
+ "grad_norm": 0.7199288606643677,
687
+ "learning_rate": 4.62748620448673e-06,
688
+ "loss": 1.1123,
689
+ "step": 970
690
+ },
691
+ {
692
+ "epoch": 2.6133333333333333,
693
+ "grad_norm": 0.8040386438369751,
694
+ "learning_rate": 4.615172843189785e-06,
695
+ "loss": 1.0573,
696
+ "step": 980
697
+ },
698
+ {
699
+ "epoch": 2.64,
700
+ "grad_norm": 0.8797423839569092,
701
+ "learning_rate": 4.602676210400126e-06,
702
+ "loss": 1.0704,
703
+ "step": 990
704
+ },
705
+ {
706
+ "epoch": 2.6666666666666665,
707
+ "grad_norm": 0.9572004079818726,
708
+ "learning_rate": 4.589997388902339e-06,
709
+ "loss": 1.0475,
710
+ "step": 1000
711
+ },
712
+ {
713
+ "epoch": 2.6933333333333334,
714
+ "grad_norm": 0.9472495913505554,
715
+ "learning_rate": 4.577137477266948e-06,
716
+ "loss": 1.0591,
717
+ "step": 1010
718
+ },
719
+ {
720
+ "epoch": 2.7199999999999998,
721
+ "grad_norm": 0.8334089517593384,
722
+ "learning_rate": 4.564097589755233e-06,
723
+ "loss": 1.062,
724
+ "step": 1020
725
+ },
726
+ {
727
+ "epoch": 2.7466666666666666,
728
+ "grad_norm": 1.1869418621063232,
729
+ "learning_rate": 4.550878856222684e-06,
730
+ "loss": 1.1608,
731
+ "step": 1030
732
+ },
733
+ {
734
+ "epoch": 2.7733333333333334,
735
+ "grad_norm": 1.0386947393417358,
736
+ "learning_rate": 4.537482422021105e-06,
737
+ "loss": 1.1039,
738
+ "step": 1040
739
+ },
740
+ {
741
+ "epoch": 2.8,
742
+ "grad_norm": 0.9129137992858887,
743
+ "learning_rate": 4.523909447899365e-06,
744
+ "loss": 1.1069,
745
+ "step": 1050
746
+ },
747
+ {
748
+ "epoch": 2.8266666666666667,
749
+ "grad_norm": 1.2377030849456787,
750
+ "learning_rate": 4.510161109902837e-06,
751
+ "loss": 1.0762,
752
+ "step": 1060
753
+ },
754
+ {
755
+ "epoch": 2.8533333333333335,
756
+ "grad_norm": 0.881824254989624,
757
+ "learning_rate": 4.496238599271485e-06,
758
+ "loss": 1.0351,
759
+ "step": 1070
760
+ },
761
+ {
762
+ "epoch": 2.88,
763
+ "grad_norm": 0.8841559886932373,
764
+ "learning_rate": 4.482143122336658e-06,
765
+ "loss": 1.0592,
766
+ "step": 1080
767
+ },
768
+ {
769
+ "epoch": 2.9066666666666667,
770
+ "grad_norm": 0.8864892721176147,
771
+ "learning_rate": 4.467875900416558e-06,
772
+ "loss": 1.0976,
773
+ "step": 1090
774
+ },
775
+ {
776
+ "epoch": 2.9333333333333336,
777
+ "grad_norm": 1.1504698991775513,
778
+ "learning_rate": 4.4534381697104255e-06,
779
+ "loss": 1.0186,
780
+ "step": 1100
781
+ },
782
+ {
783
+ "epoch": 2.96,
784
+ "grad_norm": 1.1625890731811523,
785
+ "learning_rate": 4.438831181191422e-06,
786
+ "loss": 1.0585,
787
+ "step": 1110
788
+ },
789
+ {
790
+ "epoch": 2.986666666666667,
791
+ "grad_norm": 0.9680048227310181,
792
+ "learning_rate": 4.424056200498237e-06,
793
+ "loss": 1.1027,
794
+ "step": 1120
795
+ },
796
+ {
797
+ "epoch": 3.013333333333333,
798
+ "grad_norm": 1.0091793537139893,
799
+ "learning_rate": 4.409114507825431e-06,
800
+ "loss": 1.0871,
801
+ "step": 1130
802
+ },
803
+ {
804
+ "epoch": 3.04,
805
+ "grad_norm": 0.887014627456665,
806
+ "learning_rate": 4.394007397812509e-06,
807
+ "loss": 1.1032,
808
+ "step": 1140
809
+ },
810
+ {
811
+ "epoch": 3.066666666666667,
812
+ "grad_norm": 1.0513815879821777,
813
+ "learning_rate": 4.3787361794317405e-06,
814
+ "loss": 1.0047,
815
+ "step": 1150
816
+ },
817
+ {
818
+ "epoch": 3.0933333333333333,
819
+ "grad_norm": 1.031087040901184,
820
+ "learning_rate": 4.363302175874751e-06,
821
+ "loss": 1.0925,
822
+ "step": 1160
823
+ },
824
+ {
825
+ "epoch": 3.12,
826
+ "grad_norm": 0.9170109033584595,
827
+ "learning_rate": 4.347706724437865e-06,
828
+ "loss": 1.0359,
829
+ "step": 1170
830
+ },
831
+ {
832
+ "epoch": 3.1466666666666665,
833
+ "grad_norm": 1.0121595859527588,
834
+ "learning_rate": 4.33195117640624e-06,
835
+ "loss": 1.0739,
836
+ "step": 1180
837
+ },
838
+ {
839
+ "epoch": 3.1733333333333333,
840
+ "grad_norm": 1.2087076902389526,
841
+ "learning_rate": 4.316036896936774e-06,
842
+ "loss": 1.0599,
843
+ "step": 1190
844
+ },
845
+ {
846
+ "epoch": 3.2,
847
+ "grad_norm": 1.2129995822906494,
848
+ "learning_rate": 4.299965264939834e-06,
849
+ "loss": 1.0306,
850
+ "step": 1200
851
+ },
852
+ {
853
+ "epoch": 3.2266666666666666,
854
+ "grad_norm": 1.1269701719284058,
855
+ "learning_rate": 4.283737672959766e-06,
856
+ "loss": 1.0243,
857
+ "step": 1210
858
+ },
859
+ {
860
+ "epoch": 3.2533333333333334,
861
+ "grad_norm": 1.1129047870635986,
862
+ "learning_rate": 4.267355527054243e-06,
863
+ "loss": 1.0502,
864
+ "step": 1220
865
+ },
866
+ {
867
+ "epoch": 3.2800000000000002,
868
+ "grad_norm": 0.9930374026298523,
869
+ "learning_rate": 4.250820246672433e-06,
870
+ "loss": 1.0108,
871
+ "step": 1230
872
+ },
873
+ {
874
+ "epoch": 3.3066666666666666,
875
+ "grad_norm": 1.027233600616455,
876
+ "learning_rate": 4.234133264532012e-06,
877
+ "loss": 1.0999,
878
+ "step": 1240
879
+ },
880
+ {
881
+ "epoch": 3.3333333333333335,
882
+ "grad_norm": 1.2046165466308594,
883
+ "learning_rate": 4.217296026495022e-06,
884
+ "loss": 1.0455,
885
+ "step": 1250
886
+ },
887
+ {
888
+ "epoch": 3.36,
889
+ "grad_norm": 1.0823917388916016,
890
+ "learning_rate": 4.200309991442591e-06,
891
+ "loss": 1.0443,
892
+ "step": 1260
893
+ },
894
+ {
895
+ "epoch": 3.3866666666666667,
896
+ "grad_norm": 1.0402946472167969,
897
+ "learning_rate": 4.1831766311485345e-06,
898
+ "loss": 1.0554,
899
+ "step": 1270
900
+ },
901
+ {
902
+ "epoch": 3.413333333333333,
903
+ "grad_norm": 1.111549735069275,
904
+ "learning_rate": 4.165897430151822e-06,
905
+ "loss": 1.0947,
906
+ "step": 1280
907
+ },
908
+ {
909
+ "epoch": 3.44,
910
+ "grad_norm": 1.0272332429885864,
911
+ "learning_rate": 4.148473885627952e-06,
912
+ "loss": 1.0399,
913
+ "step": 1290
914
+ },
915
+ {
916
+ "epoch": 3.466666666666667,
917
+ "grad_norm": 1.1737327575683594,
918
+ "learning_rate": 4.130907507259233e-06,
919
+ "loss": 1.0306,
920
+ "step": 1300
921
+ },
922
+ {
923
+ "epoch": 3.493333333333333,
924
+ "grad_norm": 1.2049609422683716,
925
+ "learning_rate": 4.113199817103964e-06,
926
+ "loss": 1.0165,
927
+ "step": 1310
928
+ },
929
+ {
930
+ "epoch": 3.52,
931
+ "grad_norm": 1.266038179397583,
932
+ "learning_rate": 4.095352349464564e-06,
933
+ "loss": 1.0218,
934
+ "step": 1320
935
+ },
936
+ {
937
+ "epoch": 3.546666666666667,
938
+ "grad_norm": 1.0571839809417725,
939
+ "learning_rate": 4.077366650754624e-06,
940
+ "loss": 1.0092,
941
+ "step": 1330
942
+ },
943
+ {
944
+ "epoch": 3.5733333333333333,
945
+ "grad_norm": 1.0605683326721191,
946
+ "learning_rate": 4.059244279364923e-06,
947
+ "loss": 1.0095,
948
+ "step": 1340
949
+ },
950
+ {
951
+ "epoch": 3.6,
952
+ "grad_norm": 0.9361685514450073,
953
+ "learning_rate": 4.040986805528392e-06,
954
+ "loss": 1.0308,
955
+ "step": 1350
956
+ },
957
+ {
958
+ "epoch": 3.626666666666667,
959
+ "grad_norm": 0.9611579179763794,
960
+ "learning_rate": 4.022595811184064e-06,
961
+ "loss": 1.0537,
962
+ "step": 1360
963
+ },
964
+ {
965
+ "epoch": 3.6533333333333333,
966
+ "grad_norm": 1.002272367477417,
967
+ "learning_rate": 4.004072889840006e-06,
968
+ "loss": 1.0158,
969
+ "step": 1370
970
+ },
971
+ {
972
+ "epoch": 3.68,
973
+ "grad_norm": 1.0818594694137573,
974
+ "learning_rate": 3.985419646435244e-06,
975
+ "loss": 1.0203,
976
+ "step": 1380
977
+ },
978
+ {
979
+ "epoch": 3.7066666666666666,
980
+ "grad_norm": 1.0322810411453247,
981
+ "learning_rate": 3.966637697200704e-06,
982
+ "loss": 0.9659,
983
+ "step": 1390
984
+ },
985
+ {
986
+ "epoch": 3.7333333333333334,
987
+ "grad_norm": 1.035426378250122,
988
+ "learning_rate": 3.94772866951917e-06,
989
+ "loss": 1.0147,
990
+ "step": 1400
991
+ },
992
+ {
993
+ "epoch": 3.76,
994
+ "grad_norm": 1.0693508386611938,
995
+ "learning_rate": 3.928694201784282e-06,
996
+ "loss": 0.9923,
997
+ "step": 1410
998
+ },
999
+ {
1000
+ "epoch": 3.7866666666666666,
1001
+ "grad_norm": 1.0520384311676025,
1002
+ "learning_rate": 3.909535943258567e-06,
1003
+ "loss": 1.0362,
1004
+ "step": 1420
1005
+ },
1006
+ {
1007
+ "epoch": 3.8133333333333335,
1008
+ "grad_norm": 1.161549687385559,
1009
+ "learning_rate": 3.890255553930548e-06,
1010
+ "loss": 1.0248,
1011
+ "step": 1430
1012
+ },
1013
+ {
1014
+ "epoch": 3.84,
1015
+ "grad_norm": 1.1647064685821533,
1016
+ "learning_rate": 3.870854704370902e-06,
1017
+ "loss": 1.0184,
1018
+ "step": 1440
1019
+ },
1020
+ {
1021
+ "epoch": 3.8666666666666667,
1022
+ "grad_norm": 1.0443631410598755,
1023
+ "learning_rate": 3.851335075587717e-06,
1024
+ "loss": 1.0075,
1025
+ "step": 1450
1026
+ },
1027
+ {
1028
+ "epoch": 3.8933333333333335,
1029
+ "grad_norm": 1.2016109228134155,
1030
+ "learning_rate": 3.831698358880843e-06,
1031
+ "loss": 0.9735,
1032
+ "step": 1460
1033
+ },
1034
+ {
1035
+ "epoch": 3.92,
1036
+ "grad_norm": 1.184370994567871,
1037
+ "learning_rate": 3.8119462556953358e-06,
1038
+ "loss": 1.0525,
1039
+ "step": 1470
1040
+ },
1041
+ {
1042
+ "epoch": 3.9466666666666668,
1043
+ "grad_norm": 1.0538806915283203,
1044
+ "learning_rate": 3.7920804774740427e-06,
1045
+ "loss": 1.0021,
1046
+ "step": 1480
1047
+ },
1048
+ {
1049
+ "epoch": 3.9733333333333336,
1050
+ "grad_norm": 1.1907788515090942,
1051
+ "learning_rate": 3.772102745509313e-06,
1052
+ "loss": 1.0103,
1053
+ "step": 1490
1054
+ },
1055
+ {
1056
+ "epoch": 4.0,
1057
+ "grad_norm": 0.9973454475402832,
1058
+ "learning_rate": 3.75201479079385e-06,
1059
+ "loss": 1.0488,
1060
+ "step": 1500
1061
+ },
1062
+ {
1063
+ "epoch": 4.026666666666666,
1064
+ "grad_norm": 1.0266902446746826,
1065
+ "learning_rate": 3.731818353870729e-06,
1066
+ "loss": 1.0314,
1067
+ "step": 1510
1068
+ },
1069
+ {
1070
+ "epoch": 4.053333333333334,
1071
+ "grad_norm": 1.2079659700393677,
1072
+ "learning_rate": 3.7115151846825874e-06,
1073
+ "loss": 0.9852,
1074
+ "step": 1520
1075
+ },
1076
+ {
1077
+ "epoch": 4.08,
1078
+ "grad_norm": 1.3338674306869507,
1079
+ "learning_rate": 3.6911070424199967e-06,
1080
+ "loss": 1.0028,
1081
+ "step": 1530
1082
+ },
1083
+ {
1084
+ "epoch": 4.1066666666666665,
1085
+ "grad_norm": 1.3352152109146118,
1086
+ "learning_rate": 3.6705956953690364e-06,
1087
+ "loss": 1.0209,
1088
+ "step": 1540
1089
+ },
1090
+ {
1091
+ "epoch": 4.133333333333334,
1092
+ "grad_norm": 1.1906076669692993,
1093
+ "learning_rate": 3.649982920758082e-06,
1094
+ "loss": 0.9795,
1095
+ "step": 1550
1096
+ },
1097
+ {
1098
+ "epoch": 4.16,
1099
+ "grad_norm": 1.0354583263397217,
1100
+ "learning_rate": 3.6292705046038077e-06,
1101
+ "loss": 0.978,
1102
+ "step": 1560
1103
+ },
1104
+ {
1105
+ "epoch": 4.1866666666666665,
1106
+ "grad_norm": 1.252071738243103,
1107
+ "learning_rate": 3.608460241556443e-06,
1108
+ "loss": 1.0051,
1109
+ "step": 1570
1110
+ },
1111
+ {
1112
+ "epoch": 4.213333333333333,
1113
+ "grad_norm": 0.9613018035888672,
1114
+ "learning_rate": 3.5875539347442694e-06,
1115
+ "loss": 1.0369,
1116
+ "step": 1580
1117
+ },
1118
+ {
1119
+ "epoch": 4.24,
1120
+ "grad_norm": 1.083121657371521,
1121
+ "learning_rate": 3.5665533956173857e-06,
1122
+ "loss": 1.045,
1123
+ "step": 1590
1124
+ },
1125
+ {
1126
+ "epoch": 4.266666666666667,
1127
+ "grad_norm": 1.428909182548523,
1128
+ "learning_rate": 3.5454604437907535e-06,
1129
+ "loss": 1.0239,
1130
+ "step": 1600
1131
+ },
1132
+ {
1133
+ "epoch": 4.293333333333333,
1134
+ "grad_norm": 1.4894375801086426,
1135
+ "learning_rate": 3.5242769068865375e-06,
1136
+ "loss": 1.0049,
1137
+ "step": 1610
1138
+ },
1139
+ {
1140
+ "epoch": 4.32,
1141
+ "grad_norm": 1.0027519464492798,
1142
+ "learning_rate": 3.503004620375744e-06,
1143
+ "loss": 0.9904,
1144
+ "step": 1620
1145
+ },
1146
+ {
1147
+ "epoch": 4.346666666666667,
1148
+ "grad_norm": 1.0072699785232544,
1149
+ "learning_rate": 3.481645427419188e-06,
1150
+ "loss": 0.9837,
1151
+ "step": 1630
1152
+ },
1153
+ {
1154
+ "epoch": 4.373333333333333,
1155
+ "grad_norm": 1.1597809791564941,
1156
+ "learning_rate": 3.460201178707791e-06,
1157
+ "loss": 0.9199,
1158
+ "step": 1640
1159
+ },
1160
+ {
1161
+ "epoch": 4.4,
1162
+ "grad_norm": 1.1061170101165771,
1163
+ "learning_rate": 3.438673732302223e-06,
1164
+ "loss": 1.0196,
1165
+ "step": 1650
1166
+ },
1167
+ {
1168
+ "epoch": 4.426666666666667,
1169
+ "grad_norm": 1.3632824420928955,
1170
+ "learning_rate": 3.417064953471911e-06,
1171
+ "loss": 0.987,
1172
+ "step": 1660
1173
+ },
1174
+ {
1175
+ "epoch": 4.453333333333333,
1176
+ "grad_norm": 0.9218217134475708,
1177
+ "learning_rate": 3.395376714533419e-06,
1178
+ "loss": 1.0263,
1179
+ "step": 1670
1180
+ },
1181
+ {
1182
+ "epoch": 4.48,
1183
+ "grad_norm": 1.3146958351135254,
1184
+ "learning_rate": 3.3736108946882233e-06,
1185
+ "loss": 1.0308,
1186
+ "step": 1680
1187
+ },
1188
+ {
1189
+ "epoch": 4.506666666666667,
1190
+ "grad_norm": 1.104790210723877,
1191
+ "learning_rate": 3.35176937985988e-06,
1192
+ "loss": 0.9673,
1193
+ "step": 1690
1194
+ },
1195
+ {
1196
+ "epoch": 4.533333333333333,
1197
+ "grad_norm": 1.3057141304016113,
1198
+ "learning_rate": 3.329854062530621e-06,
1199
+ "loss": 1.09,
1200
+ "step": 1700
1201
+ },
1202
+ {
1203
+ "epoch": 4.5600000000000005,
1204
+ "grad_norm": 1.2161588668823242,
1205
+ "learning_rate": 3.307866841577381e-06,
1206
+ "loss": 1.0211,
1207
+ "step": 1710
1208
+ },
1209
+ {
1210
+ "epoch": 4.586666666666667,
1211
+ "grad_norm": 1.0284647941589355,
1212
+ "learning_rate": 3.2858096221072605e-06,
1213
+ "loss": 1.0146,
1214
+ "step": 1720
1215
+ },
1216
+ {
1217
+ "epoch": 4.613333333333333,
1218
+ "grad_norm": 1.2662749290466309,
1219
+ "learning_rate": 3.2636843152924595e-06,
1220
+ "loss": 1.0113,
1221
+ "step": 1730
1222
+ },
1223
+ {
1224
+ "epoch": 4.64,
1225
+ "grad_norm": 1.086302638053894,
1226
+ "learning_rate": 3.241492838204684e-06,
1227
+ "loss": 0.9937,
1228
+ "step": 1740
1229
+ },
1230
+ {
1231
+ "epoch": 4.666666666666667,
1232
+ "grad_norm": 1.2689603567123413,
1233
+ "learning_rate": 3.2192371136490325e-06,
1234
+ "loss": 0.9909,
1235
+ "step": 1750
1236
+ },
1237
+ {
1238
+ "epoch": 4.693333333333333,
1239
+ "grad_norm": 1.1881645917892456,
1240
+ "learning_rate": 3.1969190699973985e-06,
1241
+ "loss": 0.9918,
1242
+ "step": 1760
1243
+ },
1244
+ {
1245
+ "epoch": 4.72,
1246
+ "grad_norm": 1.037034511566162,
1247
+ "learning_rate": 3.174540641021384e-06,
1248
+ "loss": 0.9945,
1249
+ "step": 1770
1250
+ },
1251
+ {
1252
+ "epoch": 4.746666666666667,
1253
+ "grad_norm": 1.156396746635437,
1254
+ "learning_rate": 3.152103765724743e-06,
1255
+ "loss": 0.9715,
1256
+ "step": 1780
1257
+ },
1258
+ {
1259
+ "epoch": 4.773333333333333,
1260
+ "grad_norm": 1.177418828010559,
1261
+ "learning_rate": 3.129610388175373e-06,
1262
+ "loss": 0.9705,
1263
+ "step": 1790
1264
+ },
1265
+ {
1266
+ "epoch": 4.8,
1267
+ "grad_norm": 1.1656800508499146,
1268
+ "learning_rate": 3.1070624573368772e-06,
1269
+ "loss": 1.0075,
1270
+ "step": 1800
1271
+ },
1272
+ {
1273
+ "epoch": 4.826666666666666,
1274
+ "grad_norm": 1.6069332361221313,
1275
+ "learning_rate": 3.0844619268996845e-06,
1276
+ "loss": 1.0066,
1277
+ "step": 1810
1278
+ },
1279
+ {
1280
+ "epoch": 4.8533333333333335,
1281
+ "grad_norm": 1.326254963874817,
1282
+ "learning_rate": 3.061810755111776e-06,
1283
+ "loss": 0.9984,
1284
+ "step": 1820
1285
+ },
1286
+ {
1287
+ "epoch": 4.88,
1288
+ "grad_norm": 1.3211278915405273,
1289
+ "learning_rate": 3.0391109046090082e-06,
1290
+ "loss": 1.0083,
1291
+ "step": 1830
1292
+ },
1293
+ {
1294
+ "epoch": 4.906666666666666,
1295
+ "grad_norm": 1.1794722080230713,
1296
+ "learning_rate": 3.016364342245059e-06,
1297
+ "loss": 1.0047,
1298
+ "step": 1840
1299
+ },
1300
+ {
1301
+ "epoch": 4.933333333333334,
1302
+ "grad_norm": 1.3180665969848633,
1303
+ "learning_rate": 2.9935730389210076e-06,
1304
+ "loss": 0.9606,
1305
+ "step": 1850
1306
+ },
1307
+ {
1308
+ "epoch": 4.96,
1309
+ "grad_norm": 1.159301996231079,
1310
+ "learning_rate": 2.970738969414563e-06,
1311
+ "loss": 1.0171,
1312
+ "step": 1860
1313
+ },
1314
+ {
1315
+ "epoch": 4.986666666666666,
1316
+ "grad_norm": 1.176303505897522,
1317
+ "learning_rate": 2.9478641122089563e-06,
1318
+ "loss": 1.0312,
1319
+ "step": 1870
1320
+ },
1321
+ {
1322
+ "epoch": 5.013333333333334,
1323
+ "grad_norm": 1.5347254276275635,
1324
+ "learning_rate": 2.924950449321515e-06,
1325
+ "loss": 0.9875,
1326
+ "step": 1880
1327
+ },
1328
+ {
1329
+ "epoch": 5.04,
1330
+ "grad_norm": 1.2689859867095947,
1331
+ "learning_rate": 2.9019999661319296e-06,
1332
+ "loss": 0.9468,
1333
+ "step": 1890
1334
+ },
1335
+ {
1336
+ "epoch": 5.066666666666666,
1337
+ "grad_norm": 1.233862280845642,
1338
+ "learning_rate": 2.8790146512102228e-06,
1339
+ "loss": 0.9642,
1340
+ "step": 1900
1341
+ },
1342
+ {
1343
+ "epoch": 5.093333333333334,
1344
+ "grad_norm": 1.0744117498397827,
1345
+ "learning_rate": 2.8559964961444533e-06,
1346
+ "loss": 0.9939,
1347
+ "step": 1910
1348
+ },
1349
+ {
1350
+ "epoch": 5.12,
1351
+ "grad_norm": 1.403465986251831,
1352
+ "learning_rate": 2.8329474953681506e-06,
1353
+ "loss": 0.9849,
1354
+ "step": 1920
1355
+ },
1356
+ {
1357
+ "epoch": 5.1466666666666665,
1358
+ "grad_norm": 1.2598626613616943,
1359
+ "learning_rate": 2.8098696459875048e-06,
1360
+ "loss": 0.9666,
1361
+ "step": 1930
1362
+ },
1363
+ {
1364
+ "epoch": 5.173333333333334,
1365
+ "grad_norm": 1.214621663093567,
1366
+ "learning_rate": 2.786764947608324e-06,
1367
+ "loss": 0.9845,
1368
+ "step": 1940
1369
+ },
1370
+ {
1371
+ "epoch": 5.2,
1372
+ "grad_norm": 1.134233832359314,
1373
+ "learning_rate": 2.7636354021627802e-06,
1374
+ "loss": 1.0092,
1375
+ "step": 1950
1376
+ },
1377
+ {
1378
+ "epoch": 5.226666666666667,
1379
+ "grad_norm": 1.0942606925964355,
1380
+ "learning_rate": 2.7404830137359445e-06,
1381
+ "loss": 1.0145,
1382
+ "step": 1960
1383
+ },
1384
+ {
1385
+ "epoch": 5.253333333333333,
1386
+ "grad_norm": 1.3385876417160034,
1387
+ "learning_rate": 2.717309788392144e-06,
1388
+ "loss": 0.9876,
1389
+ "step": 1970
1390
+ },
1391
+ {
1392
+ "epoch": 5.28,
1393
+ "grad_norm": 1.1661790609359741,
1394
+ "learning_rate": 2.694117734001143e-06,
1395
+ "loss": 1.0215,
1396
+ "step": 1980
1397
+ },
1398
+ {
1399
+ "epoch": 5.306666666666667,
1400
+ "grad_norm": 1.1474223136901855,
1401
+ "learning_rate": 2.670908860064172e-06,
1402
+ "loss": 0.9624,
1403
+ "step": 1990
1404
+ },
1405
+ {
1406
+ "epoch": 5.333333333333333,
1407
+ "grad_norm": 1.262390375137329,
1408
+ "learning_rate": 2.6476851775398073e-06,
1409
+ "loss": 0.9575,
1410
+ "step": 2000
1411
+ },
1412
+ {
1413
+ "epoch": 5.36,
1414
+ "grad_norm": 1.2726715803146362,
1415
+ "learning_rate": 2.624448698669731e-06,
1416
+ "loss": 0.9906,
1417
+ "step": 2010
1418
+ },
1419
+ {
1420
+ "epoch": 5.386666666666667,
1421
+ "grad_norm": 1.4422998428344727,
1422
+ "learning_rate": 2.6012014368043813e-06,
1423
+ "loss": 1.0085,
1424
+ "step": 2020
1425
+ },
1426
+ {
1427
+ "epoch": 5.413333333333333,
1428
+ "grad_norm": 1.073887825012207,
1429
+ "learning_rate": 2.5779454062285e-06,
1430
+ "loss": 1.0043,
1431
+ "step": 2030
1432
+ },
1433
+ {
1434
+ "epoch": 5.44,
1435
+ "grad_norm": 1.2706611156463623,
1436
+ "learning_rate": 2.5546826219866018e-06,
1437
+ "loss": 0.99,
1438
+ "step": 2040
1439
+ },
1440
+ {
1441
+ "epoch": 5.466666666666667,
1442
+ "grad_norm": 1.2542794942855835,
1443
+ "learning_rate": 2.531415099708382e-06,
1444
+ "loss": 0.9931,
1445
+ "step": 2050
1446
+ },
1447
+ {
1448
+ "epoch": 5.493333333333333,
1449
+ "grad_norm": 1.207595705986023,
1450
+ "learning_rate": 2.5081448554340688e-06,
1451
+ "loss": 1.0107,
1452
+ "step": 2060
1453
+ },
1454
+ {
1455
+ "epoch": 5.52,
1456
+ "grad_norm": 1.1939449310302734,
1457
+ "learning_rate": 2.484873905439739e-06,
1458
+ "loss": 1.0018,
1459
+ "step": 2070
1460
+ },
1461
+ {
1462
+ "epoch": 5.546666666666667,
1463
+ "grad_norm": 1.145877718925476,
1464
+ "learning_rate": 2.4616042660626176e-06,
1465
+ "loss": 0.9923,
1466
+ "step": 2080
1467
+ },
1468
+ {
1469
+ "epoch": 5.573333333333333,
1470
+ "grad_norm": 1.1784632205963135,
1471
+ "learning_rate": 2.4383379535263725e-06,
1472
+ "loss": 0.9456,
1473
+ "step": 2090
1474
+ },
1475
+ {
1476
+ "epoch": 5.6,
1477
+ "grad_norm": 1.2335214614868164,
1478
+ "learning_rate": 2.4150769837664102e-06,
1479
+ "loss": 0.9523,
1480
+ "step": 2100
1481
+ },
1482
+ {
1483
+ "epoch": 5.626666666666667,
1484
+ "grad_norm": 1.4584623575210571,
1485
+ "learning_rate": 2.391823372255208e-06,
1486
+ "loss": 0.9789,
1487
+ "step": 2110
1488
+ },
1489
+ {
1490
+ "epoch": 5.653333333333333,
1491
+ "grad_norm": 1.1800681352615356,
1492
+ "learning_rate": 2.368579133827679e-06,
1493
+ "loss": 1.0049,
1494
+ "step": 2120
1495
+ },
1496
+ {
1497
+ "epoch": 5.68,
1498
+ "grad_norm": 1.2724323272705078,
1499
+ "learning_rate": 2.3453462825065966e-06,
1500
+ "loss": 0.9843,
1501
+ "step": 2130
1502
+ },
1503
+ {
1504
+ "epoch": 5.706666666666667,
1505
+ "grad_norm": 1.3822221755981445,
1506
+ "learning_rate": 2.3221268313280836e-06,
1507
+ "loss": 0.9483,
1508
+ "step": 2140
1509
+ },
1510
+ {
1511
+ "epoch": 5.733333333333333,
1512
+ "grad_norm": 1.4377061128616333,
1513
+ "learning_rate": 2.2989227921671935e-06,
1514
+ "loss": 0.9726,
1515
+ "step": 2150
1516
+ },
1517
+ {
1518
+ "epoch": 5.76,
1519
+ "grad_norm": 1.4040346145629883,
1520
+ "learning_rate": 2.27573617556359e-06,
1521
+ "loss": 0.9877,
1522
+ "step": 2160
1523
+ },
1524
+ {
1525
+ "epoch": 5.786666666666667,
1526
+ "grad_norm": 1.2673684358596802,
1527
+ "learning_rate": 2.2525689905473377e-06,
1528
+ "loss": 0.9995,
1529
+ "step": 2170
1530
+ },
1531
+ {
1532
+ "epoch": 5.8133333333333335,
1533
+ "grad_norm": 1.2852178812026978,
1534
+ "learning_rate": 2.2294232444648316e-06,
1535
+ "loss": 0.9519,
1536
+ "step": 2180
1537
+ },
1538
+ {
1539
+ "epoch": 5.84,
1540
+ "grad_norm": 1.2947932481765747,
1541
+ "learning_rate": 2.206300942804865e-06,
1542
+ "loss": 0.968,
1543
+ "step": 2190
1544
+ },
1545
+ {
1546
+ "epoch": 5.866666666666667,
1547
+ "grad_norm": 1.0892807245254517,
1548
+ "learning_rate": 2.183204089024864e-06,
1549
+ "loss": 0.9982,
1550
+ "step": 2200
1551
+ },
1552
+ {
1553
+ "epoch": 5.8933333333333335,
1554
+ "grad_norm": 1.2275118827819824,
1555
+ "learning_rate": 2.160134684377295e-06,
1556
+ "loss": 0.9891,
1557
+ "step": 2210
1558
+ },
1559
+ {
1560
+ "epoch": 5.92,
1561
+ "grad_norm": 1.333308458328247,
1562
+ "learning_rate": 2.1370947277362646e-06,
1563
+ "loss": 0.977,
1564
+ "step": 2220
1565
+ },
1566
+ {
1567
+ "epoch": 5.946666666666666,
1568
+ "grad_norm": 1.2039783000946045,
1569
+ "learning_rate": 2.1140862154243223e-06,
1570
+ "loss": 0.9839,
1571
+ "step": 2230
1572
+ },
1573
+ {
1574
+ "epoch": 5.973333333333334,
1575
+ "grad_norm": 1.297869324684143,
1576
+ "learning_rate": 2.0911111410394915e-06,
1577
+ "loss": 0.9947,
1578
+ "step": 2240
1579
+ },
1580
+ {
1581
+ "epoch": 6.0,
1582
+ "grad_norm": 1.3803035020828247,
1583
+ "learning_rate": 2.0681714952825274e-06,
1584
+ "loss": 0.9492,
1585
+ "step": 2250
1586
+ },
1587
+ {
1588
+ "epoch": 6.026666666666666,
1589
+ "grad_norm": 1.5339772701263428,
1590
+ "learning_rate": 2.0452692657844333e-06,
1591
+ "loss": 1.0125,
1592
+ "step": 2260
1593
+ },
1594
+ {
1595
+ "epoch": 6.053333333333334,
1596
+ "grad_norm": 1.5292214155197144,
1597
+ "learning_rate": 2.0224064369342388e-06,
1598
+ "loss": 0.9575,
1599
+ "step": 2270
1600
+ },
1601
+ {
1602
+ "epoch": 6.08,
1603
+ "grad_norm": 1.2730904817581177,
1604
+ "learning_rate": 1.9995849897070616e-06,
1605
+ "loss": 0.9329,
1606
+ "step": 2280
1607
+ },
1608
+ {
1609
+ "epoch": 6.1066666666666665,
1610
+ "grad_norm": 1.529963731765747,
1611
+ "learning_rate": 1.9768069014924622e-06,
1612
+ "loss": 0.9253,
1613
+ "step": 2290
1614
+ },
1615
+ {
1616
+ "epoch": 6.133333333333334,
1617
+ "grad_norm": 1.3134512901306152,
1618
+ "learning_rate": 1.9540741459231124e-06,
1619
+ "loss": 0.9921,
1620
+ "step": 2300
1621
+ },
1622
+ {
1623
+ "epoch": 6.16,
1624
+ "grad_norm": 1.308095932006836,
1625
+ "learning_rate": 1.9313886927037843e-06,
1626
+ "loss": 0.9777,
1627
+ "step": 2310
1628
+ },
1629
+ {
1630
+ "epoch": 6.1866666666666665,
1631
+ "grad_norm": 1.4481947422027588,
1632
+ "learning_rate": 1.908752507440689e-06,
1633
+ "loss": 0.9695,
1634
+ "step": 2320
1635
+ },
1636
+ {
1637
+ "epoch": 6.213333333333333,
1638
+ "grad_norm": 1.304056167602539,
1639
+ "learning_rate": 1.8861675514711572e-06,
1640
+ "loss": 0.921,
1641
+ "step": 2330
1642
+ },
1643
+ {
1644
+ "epoch": 6.24,
1645
+ "grad_norm": 1.9694091081619263,
1646
+ "learning_rate": 1.863635781693705e-06,
1647
+ "loss": 0.9746,
1648
+ "step": 2340
1649
+ },
1650
+ {
1651
+ "epoch": 6.266666666666667,
1652
+ "grad_norm": 1.4358716011047363,
1653
+ "learning_rate": 1.8411591503984687e-06,
1654
+ "loss": 0.9828,
1655
+ "step": 2350
1656
+ },
1657
+ {
1658
+ "epoch": 6.293333333333333,
1659
+ "grad_norm": 1.2268424034118652,
1660
+ "learning_rate": 1.818739605098051e-06,
1661
+ "loss": 0.9686,
1662
+ "step": 2360
1663
+ },
1664
+ {
1665
+ "epoch": 6.32,
1666
+ "grad_norm": 1.4600015878677368,
1667
+ "learning_rate": 1.796379088358775e-06,
1668
+ "loss": 0.968,
1669
+ "step": 2370
1670
+ },
1671
+ {
1672
+ "epoch": 6.346666666666667,
1673
+ "grad_norm": 1.2927517890930176,
1674
+ "learning_rate": 1.774079537632369e-06,
1675
+ "loss": 0.9727,
1676
+ "step": 2380
1677
+ },
1678
+ {
1679
+ "epoch": 6.373333333333333,
1680
+ "grad_norm": 1.3452156782150269,
1681
+ "learning_rate": 1.7518428850880928e-06,
1682
+ "loss": 1.0324,
1683
+ "step": 2390
1684
+ },
1685
+ {
1686
+ "epoch": 6.4,
1687
+ "grad_norm": 1.2633044719696045,
1688
+ "learning_rate": 1.7296710574453262e-06,
1689
+ "loss": 0.9418,
1690
+ "step": 2400
1691
+ },
1692
+ {
1693
+ "epoch": 6.426666666666667,
1694
+ "grad_norm": 1.2620983123779297,
1695
+ "learning_rate": 1.7075659758066207e-06,
1696
+ "loss": 0.9838,
1697
+ "step": 2410
1698
+ },
1699
+ {
1700
+ "epoch": 6.453333333333333,
1701
+ "grad_norm": 1.704779863357544,
1702
+ "learning_rate": 1.6855295554912477e-06,
1703
+ "loss": 0.9787,
1704
+ "step": 2420
1705
+ },
1706
+ {
1707
+ "epoch": 6.48,
1708
+ "grad_norm": 1.4947396516799927,
1709
+ "learning_rate": 1.6635637058692417e-06,
1710
+ "loss": 0.9441,
1711
+ "step": 2430
1712
+ },
1713
+ {
1714
+ "epoch": 6.506666666666667,
1715
+ "grad_norm": 1.3541390895843506,
1716
+ "learning_rate": 1.6416703301959622e-06,
1717
+ "loss": 0.9573,
1718
+ "step": 2440
1719
+ },
1720
+ {
1721
+ "epoch": 6.533333333333333,
1722
+ "grad_norm": 1.5069646835327148,
1723
+ "learning_rate": 1.619851325447182e-06,
1724
+ "loss": 0.9402,
1725
+ "step": 2450
1726
+ },
1727
+ {
1728
+ "epoch": 6.5600000000000005,
1729
+ "grad_norm": 1.052452802658081,
1730
+ "learning_rate": 1.5981085821547237e-06,
1731
+ "loss": 1.0117,
1732
+ "step": 2460
1733
+ },
1734
+ {
1735
+ "epoch": 6.586666666666667,
1736
+ "grad_norm": 1.3735320568084717,
1737
+ "learning_rate": 1.5764439842426516e-06,
1738
+ "loss": 0.9713,
1739
+ "step": 2470
1740
+ },
1741
+ {
1742
+ "epoch": 6.613333333333333,
1743
+ "grad_norm": 1.4487781524658203,
1744
+ "learning_rate": 1.5548594088640368e-06,
1745
+ "loss": 0.9591,
1746
+ "step": 2480
1747
+ },
1748
+ {
1749
+ "epoch": 6.64,
1750
+ "grad_norm": 1.3759781122207642,
1751
+ "learning_rate": 1.5333567262383086e-06,
1752
+ "loss": 1.002,
1753
+ "step": 2490
1754
+ },
1755
+ {
1756
+ "epoch": 6.666666666666667,
1757
+ "grad_norm": 1.5115113258361816,
1758
+ "learning_rate": 1.5119377994892095e-06,
1759
+ "loss": 0.9722,
1760
+ "step": 2500
1761
+ },
1762
+ {
1763
+ "epoch": 6.693333333333333,
1764
+ "grad_norm": 1.2209426164627075,
1765
+ "learning_rate": 1.4906044844833605e-06,
1766
+ "loss": 0.9731,
1767
+ "step": 2510
1768
+ },
1769
+ {
1770
+ "epoch": 6.72,
1771
+ "grad_norm": 1.4368799924850464,
1772
+ "learning_rate": 1.4693586296694574e-06,
1773
+ "loss": 0.997,
1774
+ "step": 2520
1775
+ },
1776
+ {
1777
+ "epoch": 6.746666666666667,
1778
+ "grad_norm": 1.284833312034607,
1779
+ "learning_rate": 1.4482020759181136e-06,
1780
+ "loss": 0.9805,
1781
+ "step": 2530
1782
+ },
1783
+ {
1784
+ "epoch": 6.773333333333333,
1785
+ "grad_norm": 1.4915701150894165,
1786
+ "learning_rate": 1.4271366563623512e-06,
1787
+ "loss": 0.9859,
1788
+ "step": 2540
1789
+ },
1790
+ {
1791
+ "epoch": 6.8,
1792
+ "grad_norm": 1.3779624700546265,
1793
+ "learning_rate": 1.406164196238768e-06,
1794
+ "loss": 0.9346,
1795
+ "step": 2550
1796
+ },
1797
+ {
1798
+ "epoch": 6.826666666666666,
1799
+ "grad_norm": 1.6257760524749756,
1800
+ "learning_rate": 1.3852865127293901e-06,
1801
+ "loss": 0.9563,
1802
+ "step": 2560
1803
+ },
1804
+ {
1805
+ "epoch": 6.8533333333333335,
1806
+ "grad_norm": 1.3327535390853882,
1807
+ "learning_rate": 1.364505414804221e-06,
1808
+ "loss": 0.9809,
1809
+ "step": 2570
1810
+ },
1811
+ {
1812
+ "epoch": 6.88,
1813
+ "grad_norm": 1.8340835571289062,
1814
+ "learning_rate": 1.3438227030644946e-06,
1815
+ "loss": 0.9424,
1816
+ "step": 2580
1817
+ },
1818
+ {
1819
+ "epoch": 6.906666666666666,
1820
+ "grad_norm": 1.3357032537460327,
1821
+ "learning_rate": 1.3232401695866686e-06,
1822
+ "loss": 0.9846,
1823
+ "step": 2590
1824
+ },
1825
+ {
1826
+ "epoch": 6.933333333333334,
1827
+ "grad_norm": 1.2755762338638306,
1828
+ "learning_rate": 1.3027595977671443e-06,
1829
+ "loss": 0.94,
1830
+ "step": 2600
1831
+ },
1832
+ {
1833
+ "epoch": 6.96,
1834
+ "grad_norm": 1.5766125917434692,
1835
+ "learning_rate": 1.282382762167739e-06,
1836
+ "loss": 0.9797,
1837
+ "step": 2610
1838
+ },
1839
+ {
1840
+ "epoch": 6.986666666666666,
1841
+ "grad_norm": 1.2762746810913086,
1842
+ "learning_rate": 1.2621114283619345e-06,
1843
+ "loss": 0.9921,
1844
+ "step": 2620
1845
+ },
1846
+ {
1847
+ "epoch": 7.013333333333334,
1848
+ "grad_norm": 1.5844758749008179,
1849
+ "learning_rate": 1.241947352781889e-06,
1850
+ "loss": 0.9246,
1851
+ "step": 2630
1852
+ },
1853
+ {
1854
+ "epoch": 7.04,
1855
+ "grad_norm": 1.1820189952850342,
1856
+ "learning_rate": 1.2218922825662558e-06,
1857
+ "loss": 0.989,
1858
+ "step": 2640
1859
+ },
1860
+ {
1861
+ "epoch": 7.066666666666666,
1862
+ "grad_norm": 1.3478128910064697,
1863
+ "learning_rate": 1.2019479554087964e-06,
1864
+ "loss": 0.9711,
1865
+ "step": 2650
1866
+ },
1867
+ {
1868
+ "epoch": 7.093333333333334,
1869
+ "grad_norm": 1.191152572631836,
1870
+ "learning_rate": 1.182116099407819e-06,
1871
+ "loss": 0.9399,
1872
+ "step": 2660
1873
+ },
1874
+ {
1875
+ "epoch": 7.12,
1876
+ "grad_norm": 1.3069545030593872,
1877
+ "learning_rate": 1.1623984329164413e-06,
1878
+ "loss": 1.037,
1879
+ "step": 2670
1880
+ },
1881
+ {
1882
+ "epoch": 7.1466666666666665,
1883
+ "grad_norm": 1.3280954360961914,
1884
+ "learning_rate": 1.142796664393707e-06,
1885
+ "loss": 0.9824,
1886
+ "step": 2680
1887
+ },
1888
+ {
1889
+ "epoch": 7.173333333333334,
1890
+ "grad_norm": 1.5953059196472168,
1891
+ "learning_rate": 1.1233124922565494e-06,
1892
+ "loss": 0.9549,
1893
+ "step": 2690
1894
+ },
1895
+ {
1896
+ "epoch": 7.2,
1897
+ "grad_norm": 1.1579573154449463,
1898
+ "learning_rate": 1.1039476047326352e-06,
1899
+ "loss": 0.9626,
1900
+ "step": 2700
1901
+ },
1902
+ {
1903
+ "epoch": 7.226666666666667,
1904
+ "grad_norm": 1.3610824346542358,
1905
+ "learning_rate": 1.0847036797140832e-06,
1906
+ "loss": 0.9968,
1907
+ "step": 2710
1908
+ },
1909
+ {
1910
+ "epoch": 7.253333333333333,
1911
+ "grad_norm": 1.4503854513168335,
1912
+ "learning_rate": 1.065582384612082e-06,
1913
+ "loss": 0.8981,
1914
+ "step": 2720
1915
+ },
1916
+ {
1917
+ "epoch": 7.28,
1918
+ "grad_norm": 1.4366077184677124,
1919
+ "learning_rate": 1.0465853762124134e-06,
1920
+ "loss": 0.9544,
1921
+ "step": 2730
1922
+ },
1923
+ {
1924
+ "epoch": 7.306666666666667,
1925
+ "grad_norm": 1.6409127712249756,
1926
+ "learning_rate": 1.0277143005319038e-06,
1927
+ "loss": 0.9835,
1928
+ "step": 2740
1929
+ },
1930
+ {
1931
+ "epoch": 7.333333333333333,
1932
+ "grad_norm": 1.6304514408111572,
1933
+ "learning_rate": 1.0089707926757954e-06,
1934
+ "loss": 0.9667,
1935
+ "step": 2750
1936
+ },
1937
+ {
1938
+ "epoch": 7.36,
1939
+ "grad_norm": 1.4634387493133545,
1940
+ "learning_rate": 9.9035647669608e-07,
1941
+ "loss": 0.968,
1942
+ "step": 2760
1943
+ },
1944
+ {
1945
+ "epoch": 7.386666666666667,
1946
+ "grad_norm": 1.411413550376892,
1947
+ "learning_rate": 9.718729654507713e-07,
1948
+ "loss": 0.9681,
1949
+ "step": 2770
1950
+ },
1951
+ {
1952
+ "epoch": 7.413333333333333,
1953
+ "grad_norm": 1.3875097036361694,
1954
+ "learning_rate": 9.535218604641652e-07,
1955
+ "loss": 0.9676,
1956
+ "step": 2780
1957
+ },
1958
+ {
1959
+ "epoch": 7.44,
1960
+ "grad_norm": 1.4006201028823853,
1961
+ "learning_rate": 9.353047517880709e-07,
1962
+ "loss": 0.9615,
1963
+ "step": 2790
1964
+ },
1965
+ {
1966
+ "epoch": 7.466666666666667,
1967
+ "grad_norm": 1.580459713935852,
1968
+ "learning_rate": 9.172232178640361e-07,
1969
+ "loss": 0.9638,
1970
+ "step": 2800
1971
+ },
1972
+ {
1973
+ "epoch": 7.493333333333333,
1974
+ "grad_norm": 1.4033180475234985,
1975
+ "learning_rate": 8.992788253865872e-07,
1976
+ "loss": 0.9885,
1977
+ "step": 2810
1978
+ },
1979
+ {
1980
+ "epoch": 7.52,
1981
+ "grad_norm": 1.7243731021881104,
1982
+ "learning_rate": 8.814731291674756e-07,
1983
+ "loss": 0.9464,
1984
+ "step": 2820
1985
+ },
1986
+ {
1987
+ "epoch": 7.546666666666667,
1988
+ "grad_norm": 1.453606367111206,
1989
+ "learning_rate": 8.63807672000963e-07,
1990
+ "loss": 0.9594,
1991
+ "step": 2830
1992
+ },
1993
+ {
1994
+ "epoch": 7.573333333333333,
1995
+ "grad_norm": 1.6155478954315186,
1996
+ "learning_rate": 8.462839845301438e-07,
1997
+ "loss": 0.9609,
1998
+ "step": 2840
1999
+ },
2000
+ {
2001
+ "epoch": 7.6,
2002
+ "grad_norm": 1.4838684797286987,
2003
+ "learning_rate": 8.289035851143198e-07,
2004
+ "loss": 0.9643,
2005
+ "step": 2850
2006
+ },
2007
+ {
2008
+ "epoch": 7.626666666666667,
2009
+ "grad_norm": 1.3259801864624023,
2010
+ "learning_rate": 8.116679796974389e-07,
2011
+ "loss": 0.9646,
2012
+ "step": 2860
2013
+ },
2014
+ {
2015
+ "epoch": 7.653333333333333,
2016
+ "grad_norm": 1.5047879219055176,
2017
+ "learning_rate": 7.945786616776157e-07,
2018
+ "loss": 0.9062,
2019
+ "step": 2870
2020
+ },
2021
+ {
2022
+ "epoch": 7.68,
2023
+ "grad_norm": 1.5503374338150024,
2024
+ "learning_rate": 7.776371117777276e-07,
2025
+ "loss": 0.9242,
2026
+ "step": 2880
2027
+ },
2028
+ {
2029
+ "epoch": 7.706666666666667,
2030
+ "grad_norm": 1.6389449834823608,
2031
+ "learning_rate": 7.60844797917123e-07,
2032
+ "loss": 0.9476,
2033
+ "step": 2890
2034
+ },
2035
+ {
2036
+ "epoch": 7.733333333333333,
2037
+ "grad_norm": 1.2944670915603638,
2038
+ "learning_rate": 7.442031750844269e-07,
2039
+ "loss": 0.974,
2040
+ "step": 2900
2041
+ },
2042
+ {
2043
+ "epoch": 7.76,
2044
+ "grad_norm": 1.4704028367996216,
2045
+ "learning_rate": 7.277136852114747e-07,
2046
+ "loss": 0.9126,
2047
+ "step": 2910
2048
+ },
2049
+ {
2050
+ "epoch": 7.786666666666667,
2051
+ "grad_norm": 1.8540769815444946,
2052
+ "learning_rate": 7.113777570483701e-07,
2053
+ "loss": 0.9673,
2054
+ "step": 2920
2055
+ },
2056
+ {
2057
+ "epoch": 7.8133333333333335,
2058
+ "grad_norm": 1.45095694065094,
2059
+ "learning_rate": 6.951968060396963e-07,
2060
+ "loss": 0.9677,
2061
+ "step": 2930
2062
+ },
2063
+ {
2064
+ "epoch": 7.84,
2065
+ "grad_norm": 1.4591078758239746,
2066
+ "learning_rate": 6.791722342018656e-07,
2067
+ "loss": 1.0081,
2068
+ "step": 2940
2069
+ },
2070
+ {
2071
+ "epoch": 7.866666666666667,
2072
+ "grad_norm": 1.3265269994735718,
2073
+ "learning_rate": 6.633054300016464e-07,
2074
+ "loss": 0.9352,
2075
+ "step": 2950
2076
+ },
2077
+ {
2078
+ "epoch": 7.8933333333333335,
2079
+ "grad_norm": 1.5188606977462769,
2080
+ "learning_rate": 6.475977682358558e-07,
2081
+ "loss": 0.9725,
2082
+ "step": 2960
2083
+ },
2084
+ {
2085
+ "epoch": 7.92,
2086
+ "grad_norm": 1.5498340129852295,
2087
+ "learning_rate": 6.320506099122359e-07,
2088
+ "loss": 0.9883,
2089
+ "step": 2970
2090
+ },
2091
+ {
2092
+ "epoch": 7.946666666666666,
2093
+ "grad_norm": 1.5423794984817505,
2094
+ "learning_rate": 6.166653021315336e-07,
2095
+ "loss": 0.9092,
2096
+ "step": 2980
2097
+ },
2098
+ {
2099
+ "epoch": 7.973333333333334,
2100
+ "grad_norm": 1.4549285173416138,
2101
+ "learning_rate": 6.01443177970773e-07,
2102
+ "loss": 0.9351,
2103
+ "step": 2990
2104
+ },
2105
+ {
2106
+ "epoch": 8.0,
2107
+ "grad_norm": 1.2420357465744019,
2108
+ "learning_rate": 5.863855563677559e-07,
2109
+ "loss": 0.9546,
2110
+ "step": 3000
2111
+ },
2112
+ {
2113
+ "epoch": 8.026666666666667,
2114
+ "grad_norm": 1.233181357383728,
2115
+ "learning_rate": 5.714937420067746e-07,
2116
+ "loss": 0.916,
2117
+ "step": 3010
2118
+ },
2119
+ {
2120
+ "epoch": 8.053333333333333,
2121
+ "grad_norm": 1.1143083572387695,
2122
+ "learning_rate": 5.567690252055738e-07,
2123
+ "loss": 0.9752,
2124
+ "step": 3020
2125
+ },
2126
+ {
2127
+ "epoch": 8.08,
2128
+ "grad_norm": 1.7582933902740479,
2129
+ "learning_rate": 5.422126818035403e-07,
2130
+ "loss": 0.907,
2131
+ "step": 3030
2132
+ },
2133
+ {
2134
+ "epoch": 8.106666666666667,
2135
+ "grad_norm": 1.5106295347213745,
2136
+ "learning_rate": 5.278259730511651e-07,
2137
+ "loss": 0.9487,
2138
+ "step": 3040
2139
+ },
2140
+ {
2141
+ "epoch": 8.133333333333333,
2142
+ "grad_norm": 1.3198901414871216,
2143
+ "learning_rate": 5.136101455007541e-07,
2144
+ "loss": 0.922,
2145
+ "step": 3050
2146
+ },
2147
+ {
2148
+ "epoch": 8.16,
2149
+ "grad_norm": 1.433039665222168,
2150
+ "learning_rate": 4.995664308984254e-07,
2151
+ "loss": 0.912,
2152
+ "step": 3060
2153
+ },
2154
+ {
2155
+ "epoch": 8.186666666666667,
2156
+ "grad_norm": 1.372050404548645,
2157
+ "learning_rate": 4.856960460773766e-07,
2158
+ "loss": 0.9788,
2159
+ "step": 3070
2160
+ },
2161
+ {
2162
+ "epoch": 8.213333333333333,
2163
+ "grad_norm": 1.4133652448654175,
2164
+ "learning_rate": 4.7200019285245867e-07,
2165
+ "loss": 0.9483,
2166
+ "step": 3080
2167
+ },
2168
+ {
2169
+ "epoch": 8.24,
2170
+ "grad_norm": 1.8541817665100098,
2171
+ "learning_rate": 4.5848005791603533e-07,
2172
+ "loss": 0.9734,
2173
+ "step": 3090
2174
+ },
2175
+ {
2176
+ "epoch": 8.266666666666667,
2177
+ "grad_norm": 1.7887778282165527,
2178
+ "learning_rate": 4.451368127351674e-07,
2179
+ "loss": 1.0254,
2180
+ "step": 3100
2181
+ },
2182
+ {
2183
+ "epoch": 8.293333333333333,
2184
+ "grad_norm": 1.3291224241256714,
2185
+ "learning_rate": 4.319716134501051e-07,
2186
+ "loss": 0.969,
2187
+ "step": 3110
2188
+ },
2189
+ {
2190
+ "epoch": 8.32,
2191
+ "grad_norm": 1.4450148344039917,
2192
+ "learning_rate": 4.1898560077411664e-07,
2193
+ "loss": 0.9059,
2194
+ "step": 3120
2195
+ },
2196
+ {
2197
+ "epoch": 8.346666666666668,
2198
+ "grad_norm": 1.4905790090560913,
2199
+ "learning_rate": 4.061798998946459e-07,
2200
+ "loss": 0.9379,
2201
+ "step": 3130
2202
+ },
2203
+ {
2204
+ "epoch": 8.373333333333333,
2205
+ "grad_norm": 1.5517672300338745,
2206
+ "learning_rate": 3.935556203758237e-07,
2207
+ "loss": 0.9874,
2208
+ "step": 3140
2209
+ },
2210
+ {
2211
+ "epoch": 8.4,
2212
+ "grad_norm": 1.5111827850341797,
2213
+ "learning_rate": 3.8111385606232565e-07,
2214
+ "loss": 0.9313,
2215
+ "step": 3150
2216
+ },
2217
+ {
2218
+ "epoch": 8.426666666666666,
2219
+ "grad_norm": 1.3383586406707764,
2220
+ "learning_rate": 3.6885568498459395e-07,
2221
+ "loss": 0.9489,
2222
+ "step": 3160
2223
+ },
2224
+ {
2225
+ "epoch": 8.453333333333333,
2226
+ "grad_norm": 1.7002395391464233,
2227
+ "learning_rate": 3.5678216926543384e-07,
2228
+ "loss": 0.9954,
2229
+ "step": 3170
2230
+ },
2231
+ {
2232
+ "epoch": 8.48,
2233
+ "grad_norm": 1.522956371307373,
2234
+ "learning_rate": 3.448943550279804e-07,
2235
+ "loss": 0.9239,
2236
+ "step": 3180
2237
+ },
2238
+ {
2239
+ "epoch": 8.506666666666666,
2240
+ "grad_norm": 1.3977686166763306,
2241
+ "learning_rate": 3.331932723050596e-07,
2242
+ "loss": 0.9494,
2243
+ "step": 3190
2244
+ },
2245
+ {
2246
+ "epoch": 8.533333333333333,
2247
+ "grad_norm": 1.385392427444458,
2248
+ "learning_rate": 3.216799349499383e-07,
2249
+ "loss": 1.0081,
2250
+ "step": 3200
2251
+ },
2252
+ {
2253
+ "epoch": 8.56,
2254
+ "grad_norm": 1.3390395641326904,
2255
+ "learning_rate": 3.1035534054847884e-07,
2256
+ "loss": 0.9623,
2257
+ "step": 3210
2258
+ },
2259
+ {
2260
+ "epoch": 8.586666666666666,
2261
+ "grad_norm": 1.3952502012252808,
2262
+ "learning_rate": 2.992204703326995e-07,
2263
+ "loss": 0.953,
2264
+ "step": 3220
2265
+ },
2266
+ {
2267
+ "epoch": 8.613333333333333,
2268
+ "grad_norm": 1.281001329421997,
2269
+ "learning_rate": 2.882762890957586e-07,
2270
+ "loss": 1.0032,
2271
+ "step": 3230
2272
+ },
2273
+ {
2274
+ "epoch": 8.64,
2275
+ "grad_norm": 1.4301480054855347,
2276
+ "learning_rate": 2.7752374510835456e-07,
2277
+ "loss": 0.9094,
2278
+ "step": 3240
2279
+ },
2280
+ {
2281
+ "epoch": 8.666666666666666,
2282
+ "grad_norm": 1.2691582441329956,
2283
+ "learning_rate": 2.6696377003656654e-07,
2284
+ "loss": 0.9169,
2285
+ "step": 3250
2286
+ },
2287
+ {
2288
+ "epoch": 8.693333333333333,
2289
+ "grad_norm": 1.4293104410171509,
2290
+ "learning_rate": 2.565972788611243e-07,
2291
+ "loss": 0.9849,
2292
+ "step": 3260
2293
+ },
2294
+ {
2295
+ "epoch": 8.72,
2296
+ "grad_norm": 1.213094711303711,
2297
+ "learning_rate": 2.46425169798134e-07,
2298
+ "loss": 0.9507,
2299
+ "step": 3270
2300
+ },
2301
+ {
2302
+ "epoch": 8.746666666666666,
2303
+ "grad_norm": 1.4834156036376953,
2304
+ "learning_rate": 2.3644832422124565e-07,
2305
+ "loss": 0.9814,
2306
+ "step": 3280
2307
+ },
2308
+ {
2309
+ "epoch": 8.773333333333333,
2310
+ "grad_norm": 1.3371623754501343,
2311
+ "learning_rate": 2.2666760658529103e-07,
2312
+ "loss": 0.952,
2313
+ "step": 3290
2314
+ },
2315
+ {
2316
+ "epoch": 8.8,
2317
+ "grad_norm": 1.2769241333007812,
2318
+ "learning_rate": 2.1708386435137647e-07,
2319
+ "loss": 0.9713,
2320
+ "step": 3300
2321
+ },
2322
+ {
2323
+ "epoch": 8.826666666666666,
2324
+ "grad_norm": 1.410171627998352,
2325
+ "learning_rate": 2.0769792791345945e-07,
2326
+ "loss": 0.9523,
2327
+ "step": 3310
2328
+ },
2329
+ {
2330
+ "epoch": 8.853333333333333,
2331
+ "grad_norm": 1.3789598941802979,
2332
+ "learning_rate": 1.9851061052639202e-07,
2333
+ "loss": 1.0252,
2334
+ "step": 3320
2335
+ },
2336
+ {
2337
+ "epoch": 8.88,
2338
+ "grad_norm": 1.4115532636642456,
2339
+ "learning_rate": 1.8952270823546253e-07,
2340
+ "loss": 0.9217,
2341
+ "step": 3330
2342
+ },
2343
+ {
2344
+ "epoch": 8.906666666666666,
2345
+ "grad_norm": 1.686996340751648,
2346
+ "learning_rate": 1.8073499980741426e-07,
2347
+ "loss": 0.9918,
2348
+ "step": 3340
2349
+ },
2350
+ {
2351
+ "epoch": 8.933333333333334,
2352
+ "grad_norm": 1.3518773317337036,
2353
+ "learning_rate": 1.721482466629737e-07,
2354
+ "loss": 0.9355,
2355
+ "step": 3350
2356
+ },
2357
+ {
2358
+ "epoch": 8.96,
2359
+ "grad_norm": 1.308510184288025,
2360
+ "learning_rate": 1.637631928108721e-07,
2361
+ "loss": 0.9804,
2362
+ "step": 3360
2363
+ },
2364
+ {
2365
+ "epoch": 8.986666666666666,
2366
+ "grad_norm": 1.519740104675293,
2367
+ "learning_rate": 1.5558056478338523e-07,
2368
+ "loss": 0.9214,
2369
+ "step": 3370
2370
+ },
2371
+ {
2372
+ "epoch": 9.013333333333334,
2373
+ "grad_norm": 1.4635462760925293,
2374
+ "learning_rate": 1.476010715733761e-07,
2375
+ "loss": 0.9473,
2376
+ "step": 3380
2377
+ },
2378
+ {
2379
+ "epoch": 9.04,
2380
+ "grad_norm": 1.6289703845977783,
2381
+ "learning_rate": 1.3982540457286893e-07,
2382
+ "loss": 1.0251,
2383
+ "step": 3390
2384
+ },
2385
+ {
2386
+ "epoch": 9.066666666666666,
2387
+ "grad_norm": 1.1922096014022827,
2388
+ "learning_rate": 1.3225423751313942e-07,
2389
+ "loss": 0.9078,
2390
+ "step": 3400
2391
+ },
2392
+ {
2393
+ "epoch": 9.093333333333334,
2394
+ "grad_norm": 1.4207053184509277,
2395
+ "learning_rate": 1.248882264063389e-07,
2396
+ "loss": 0.9616,
2397
+ "step": 3410
2398
+ },
2399
+ {
2400
+ "epoch": 9.12,
2401
+ "grad_norm": 1.662922739982605,
2402
+ "learning_rate": 1.1772800948865542e-07,
2403
+ "loss": 0.9826,
2404
+ "step": 3420
2405
+ },
2406
+ {
2407
+ "epoch": 9.146666666666667,
2408
+ "grad_norm": 1.499869704246521,
2409
+ "learning_rate": 1.1077420716501031e-07,
2410
+ "loss": 0.9619,
2411
+ "step": 3430
2412
+ },
2413
+ {
2414
+ "epoch": 9.173333333333334,
2415
+ "grad_norm": 1.6088509559631348,
2416
+ "learning_rate": 1.0402742195530501e-07,
2417
+ "loss": 0.9319,
2418
+ "step": 3440
2419
+ },
2420
+ {
2421
+ "epoch": 9.2,
2422
+ "grad_norm": 1.6875691413879395,
2423
+ "learning_rate": 9.748823844221239e-08,
2424
+ "loss": 0.9762,
2425
+ "step": 3450
2426
+ },
2427
+ {
2428
+ "epoch": 9.226666666666667,
2429
+ "grad_norm": 1.240744709968567,
2430
+ "learning_rate": 9.115722322052878e-08,
2431
+ "loss": 0.9661,
2432
+ "step": 3460
2433
+ },
2434
+ {
2435
+ "epoch": 9.253333333333334,
2436
+ "grad_norm": 1.5115891695022583,
2437
+ "learning_rate": 8.503492484807613e-08,
2438
+ "loss": 0.9694,
2439
+ "step": 3470
2440
+ },
2441
+ {
2442
+ "epoch": 9.28,
2443
+ "grad_norm": 1.4953974485397339,
2444
+ "learning_rate": 7.912187379817582e-08,
2445
+ "loss": 0.9815,
2446
+ "step": 3480
2447
+ },
2448
+ {
2449
+ "epoch": 9.306666666666667,
2450
+ "grad_norm": 1.2569257020950317,
2451
+ "learning_rate": 7.341858241368182e-08,
2452
+ "loss": 0.9463,
2453
+ "step": 3490
2454
+ },
2455
+ {
2456
+ "epoch": 9.333333333333334,
2457
+ "grad_norm": 1.4589368104934692,
2458
+ "learning_rate": 6.79255448625904e-08,
2459
+ "loss": 0.9505,
2460
+ "step": 3500
2461
+ },
2462
+ {
2463
+ "epoch": 9.36,
2464
+ "grad_norm": 1.5550317764282227,
2465
+ "learning_rate": 6.264323709522125e-08,
2466
+ "loss": 0.9576,
2467
+ "step": 3510
2468
+ },
2469
+ {
2470
+ "epoch": 9.386666666666667,
2471
+ "grad_norm": 1.359791874885559,
2472
+ "learning_rate": 5.7572116802979695e-08,
2473
+ "loss": 0.9569,
2474
+ "step": 3520
2475
+ },
2476
+ {
2477
+ "epoch": 9.413333333333334,
2478
+ "grad_norm": 1.360062837600708,
2479
+ "learning_rate": 5.2712623378697035e-08,
2480
+ "loss": 0.9108,
2481
+ "step": 3530
2482
+ },
2483
+ {
2484
+ "epoch": 9.44,
2485
+ "grad_norm": 1.419716238975525,
2486
+ "learning_rate": 4.806517787856152e-08,
2487
+ "loss": 0.999,
2488
+ "step": 3540
2489
+ },
2490
+ {
2491
+ "epoch": 9.466666666666667,
2492
+ "grad_norm": 1.3147867918014526,
2493
+ "learning_rate": 4.3630182985633093e-08,
2494
+ "loss": 0.9516,
2495
+ "step": 3550
2496
+ },
2497
+ {
2498
+ "epoch": 9.493333333333334,
2499
+ "grad_norm": 1.3970048427581787,
2500
+ "learning_rate": 3.940802297495466e-08,
2501
+ "loss": 0.9381,
2502
+ "step": 3560
2503
+ },
2504
+ {
2505
+ "epoch": 9.52,
2506
+ "grad_norm": 1.278246283531189,
2507
+ "learning_rate": 3.539906368025453e-08,
2508
+ "loss": 0.9293,
2509
+ "step": 3570
2510
+ },
2511
+ {
2512
+ "epoch": 9.546666666666667,
2513
+ "grad_norm": 1.3652037382125854,
2514
+ "learning_rate": 3.1603652462249e-08,
2515
+ "loss": 0.9309,
2516
+ "step": 3580
2517
+ },
2518
+ {
2519
+ "epoch": 9.573333333333334,
2520
+ "grad_norm": 1.4681710004806519,
2521
+ "learning_rate": 2.802211817854561e-08,
2522
+ "loss": 0.9415,
2523
+ "step": 3590
2524
+ },
2525
+ {
2526
+ "epoch": 9.6,
2527
+ "grad_norm": 1.4077391624450684,
2528
+ "learning_rate": 2.465477115514675e-08,
2529
+ "loss": 0.9555,
2530
+ "step": 3600
2531
+ },
2532
+ {
2533
+ "epoch": 9.626666666666667,
2534
+ "grad_norm": 1.8016074895858765,
2535
+ "learning_rate": 2.1501903159563688e-08,
2536
+ "loss": 0.9258,
2537
+ "step": 3610
2538
+ },
2539
+ {
2540
+ "epoch": 9.653333333333332,
2541
+ "grad_norm": 1.37924325466156,
2542
+ "learning_rate": 1.856378737553427e-08,
2543
+ "loss": 0.9798,
2544
+ "step": 3620
2545
+ },
2546
+ {
2547
+ "epoch": 9.68,
2548
+ "grad_norm": 1.2986595630645752,
2549
+ "learning_rate": 1.584067837935327e-08,
2550
+ "loss": 0.9444,
2551
+ "step": 3630
2552
+ },
2553
+ {
2554
+ "epoch": 9.706666666666667,
2555
+ "grad_norm": 1.3296507596969604,
2556
+ "learning_rate": 1.3332812117814731e-08,
2557
+ "loss": 0.9421,
2558
+ "step": 3640
2559
+ },
2560
+ {
2561
+ "epoch": 9.733333333333333,
2562
+ "grad_norm": 1.47772216796875,
2563
+ "learning_rate": 1.1040405887767503e-08,
2564
+ "loss": 0.8807,
2565
+ "step": 3650
2566
+ },
2567
+ {
2568
+ "epoch": 9.76,
2569
+ "grad_norm": 1.6291658878326416,
2570
+ "learning_rate": 8.963658317286684e-09,
2571
+ "loss": 0.9037,
2572
+ "step": 3660
2573
+ },
2574
+ {
2575
+ "epoch": 9.786666666666667,
2576
+ "grad_norm": 1.5793346166610718,
2577
+ "learning_rate": 7.102749348465166e-09,
2578
+ "loss": 0.9839,
2579
+ "step": 3670
2580
+ },
2581
+ {
2582
+ "epoch": 9.813333333333333,
2583
+ "grad_norm": 1.3573871850967407,
2584
+ "learning_rate": 5.457840221820831e-09,
2585
+ "loss": 0.9405,
2586
+ "step": 3680
2587
+ },
2588
+ {
2589
+ "epoch": 9.84,
2590
+ "grad_norm": 1.3204113245010376,
2591
+ "learning_rate": 4.029073462325506e-09,
2592
+ "loss": 0.9589,
2593
+ "step": 3690
2594
+ },
2595
+ {
2596
+ "epoch": 9.866666666666667,
2597
+ "grad_norm": 1.4250832796096802,
2598
+ "learning_rate": 2.8165728670573324e-09,
2599
+ "loss": 0.8948,
2600
+ "step": 3700
2601
+ },
2602
+ {
2603
+ "epoch": 9.893333333333333,
2604
+ "grad_norm": 1.9013235569000244,
2605
+ "learning_rate": 1.8204434944729676e-09,
2606
+ "loss": 1.0401,
2607
+ "step": 3710
2608
+ },
2609
+ {
2610
+ "epoch": 9.92,
2611
+ "grad_norm": 1.3507270812988281,
2612
+ "learning_rate": 1.0407716553040291e-09,
2613
+ "loss": 0.9874,
2614
+ "step": 3720
2615
+ },
2616
+ {
2617
+ "epoch": 9.946666666666667,
2618
+ "grad_norm": 1.3722429275512695,
2619
+ "learning_rate": 4.77624905080576e-10,
2620
+ "loss": 0.9466,
2621
+ "step": 3730
2622
+ },
2623
+ {
2624
+ "epoch": 9.973333333333333,
2625
+ "grad_norm": 1.249128818511963,
2626
+ "learning_rate": 1.3105203827634693e-10,
2627
+ "loss": 0.9351,
2628
+ "step": 3740
2629
+ },
2630
+ {
2631
+ "epoch": 10.0,
2632
+ "grad_norm": 1.5156923532485962,
2633
+ "learning_rate": 1.0830840810327482e-12,
2634
+ "loss": 0.9953,
2635
+ "step": 3750
2636
+ }
2637
+ ],
2638
+ "logging_steps": 10,
2639
+ "max_steps": 3750,
2640
+ "num_input_tokens_seen": 0,
2641
+ "num_train_epochs": 10,
2642
+ "save_steps": 500,
2643
+ "stateful_callbacks": {
2644
+ "TrainerControl": {
2645
+ "args": {
2646
+ "should_epoch_stop": false,
2647
+ "should_evaluate": false,
2648
+ "should_log": false,
2649
+ "should_save": true,
2650
+ "should_training_stop": true
2651
+ },
2652
+ "attributes": {}
2653
+ }
2654
+ },
2655
+ "total_flos": 3.3564794130805555e+17,
2656
+ "train_batch_size": 8,
2657
+ "trial_name": null,
2658
+ "trial_params": null
2659
+ }
Direction/Ageis_Danger/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9f95f06ecbe5d43fe2559731e992e8aee53d0efb541c4475216a0fb6c1b74b34
3
+ size 5880
Direction/Ageis_Danger/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
Direction/Beaver-Danger/README.md ADDED
@@ -0,0 +1,208 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/jzc/model/Qwen3-8B
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:/workspace/jzc/model/Qwen3-8B
7
+ - llama-factory
8
+ - lora
9
+ - transformers
10
+ ---
11
+
12
+ # Model Card for Model ID
13
+
14
+ <!-- Provide a quick summary of what the model is/does. -->
15
+
16
+
17
+
18
+ ## Model Details
19
+
20
+ ### Model Description
21
+
22
+ <!-- Provide a longer summary of what this model is. -->
23
+
24
+
25
+
26
+ - **Developed by:** [More Information Needed]
27
+ - **Funded by [optional]:** [More Information Needed]
28
+ - **Shared by [optional]:** [More Information Needed]
29
+ - **Model type:** [More Information Needed]
30
+ - **Language(s) (NLP):** [More Information Needed]
31
+ - **License:** [More Information Needed]
32
+ - **Finetuned from model [optional]:** [More Information Needed]
33
+
34
+ ### Model Sources [optional]
35
+
36
+ <!-- Provide the basic links for the model. -->
37
+
38
+ - **Repository:** [More Information Needed]
39
+ - **Paper [optional]:** [More Information Needed]
40
+ - **Demo [optional]:** [More Information Needed]
41
+
42
+ ## Uses
43
+
44
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
45
+
46
+ ### Direct Use
47
+
48
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Downstream Use [optional]
53
+
54
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
55
+
56
+ [More Information Needed]
57
+
58
+ ### Out-of-Scope Use
59
+
60
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ## Bias, Risks, and Limitations
65
+
66
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
67
+
68
+ [More Information Needed]
69
+
70
+ ### Recommendations
71
+
72
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
73
+
74
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
75
+
76
+ ## How to Get Started with the Model
77
+
78
+ Use the code below to get started with the model.
79
+
80
+ [More Information Needed]
81
+
82
+ ## Training Details
83
+
84
+ ### Training Data
85
+
86
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
87
+
88
+ [More Information Needed]
89
+
90
+ ### Training Procedure
91
+
92
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
93
+
94
+ #### Preprocessing [optional]
95
+
96
+ [More Information Needed]
97
+
98
+
99
+ #### Training Hyperparameters
100
+
101
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
102
+
103
+ #### Speeds, Sizes, Times [optional]
104
+
105
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
106
+
107
+ [More Information Needed]
108
+
109
+ ## Evaluation
110
+
111
+ <!-- This section describes the evaluation protocols and provides the results. -->
112
+
113
+ ### Testing Data, Factors & Metrics
114
+
115
+ #### Testing Data
116
+
117
+ <!-- This should link to a Dataset Card if possible. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Factors
122
+
123
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
124
+
125
+ [More Information Needed]
126
+
127
+ #### Metrics
128
+
129
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
130
+
131
+ [More Information Needed]
132
+
133
+ ### Results
134
+
135
+ [More Information Needed]
136
+
137
+ #### Summary
138
+
139
+
140
+
141
+ ## Model Examination [optional]
142
+
143
+ <!-- Relevant interpretability work for the model goes here -->
144
+
145
+ [More Information Needed]
146
+
147
+ ## Environmental Impact
148
+
149
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
150
+
151
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
152
+
153
+ - **Hardware Type:** [More Information Needed]
154
+ - **Hours used:** [More Information Needed]
155
+ - **Cloud Provider:** [More Information Needed]
156
+ - **Compute Region:** [More Information Needed]
157
+ - **Carbon Emitted:** [More Information Needed]
158
+
159
+ ## Technical Specifications [optional]
160
+
161
+ ### Model Architecture and Objective
162
+
163
+ [More Information Needed]
164
+
165
+ ### Compute Infrastructure
166
+
167
+ [More Information Needed]
168
+
169
+ #### Hardware
170
+
171
+ [More Information Needed]
172
+
173
+ #### Software
174
+
175
+ [More Information Needed]
176
+
177
+ ## Citation [optional]
178
+
179
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
180
+
181
+ **BibTeX:**
182
+
183
+ [More Information Needed]
184
+
185
+ **APA:**
186
+
187
+ [More Information Needed]
188
+
189
+ ## Glossary [optional]
190
+
191
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
192
+
193
+ [More Information Needed]
194
+
195
+ ## More Information [optional]
196
+
197
+ [More Information Needed]
198
+
199
+ ## Model Card Authors [optional]
200
+
201
+ [More Information Needed]
202
+
203
+ ## Model Card Contact
204
+
205
+ [More Information Needed]
206
+ ### Framework versions
207
+
208
+ - PEFT 0.17.1
Direction/Beaver-Danger/adapter_config.json ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/jzc/model/Qwen3-8B",
5
+ "bias": "none",
6
+ "corda_config": null,
7
+ "eva_config": null,
8
+ "exclude_modules": null,
9
+ "fan_in_fan_out": false,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 16,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0.0,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "qalora_group_size": 16,
24
+ "r": 8,
25
+ "rank_pattern": {},
26
+ "revision": null,
27
+ "target_modules": [
28
+ "down_proj",
29
+ "v_proj",
30
+ "k_proj",
31
+ "o_proj",
32
+ "up_proj",
33
+ "gate_proj",
34
+ "q_proj"
35
+ ],
36
+ "target_parameters": null,
37
+ "task_type": "CAUSAL_LM",
38
+ "trainable_token_indices": null,
39
+ "use_dora": false,
40
+ "use_qalora": false,
41
+ "use_rslora": false
42
+ }
Direction/Beaver-Danger/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c4497dc97b43f46af20be10a5eaad6f94816cf24913c270af3e3c584a8bf66e0
3
+ size 87360584
Direction/Beaver-Danger/added_tokens.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</think>": 151668,
3
+ "</tool_call>": 151658,
4
+ "</tool_response>": 151666,
5
+ "<think>": 151667,
6
+ "<tool_call>": 151657,
7
+ "<tool_response>": 151665,
8
+ "<|box_end|>": 151649,
9
+ "<|box_start|>": 151648,
10
+ "<|endoftext|>": 151643,
11
+ "<|file_sep|>": 151664,
12
+ "<|fim_middle|>": 151660,
13
+ "<|fim_pad|>": 151662,
14
+ "<|fim_prefix|>": 151659,
15
+ "<|fim_suffix|>": 151661,
16
+ "<|im_end|>": 151645,
17
+ "<|im_start|>": 151644,
18
+ "<|image_pad|>": 151655,
19
+ "<|object_ref_end|>": 151647,
20
+ "<|object_ref_start|>": 151646,
21
+ "<|quad_end|>": 151651,
22
+ "<|quad_start|>": 151650,
23
+ "<|repo_name|>": 151663,
24
+ "<|video_pad|>": 151656,
25
+ "<|vision_end|>": 151653,
26
+ "<|vision_pad|>": 151654,
27
+ "<|vision_start|>": 151652
28
+ }
Direction/Beaver-Danger/chat_template.jinja ADDED
@@ -0,0 +1,89 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0].role == 'system' %}
4
+ {{- messages[0].content + '\n\n' }}
5
+ {%- endif %}
6
+ {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
7
+ {%- for tool in tools %}
8
+ {{- "\n" }}
9
+ {{- tool | tojson }}
10
+ {%- endfor %}
11
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
12
+ {%- else %}
13
+ {%- if messages[0].role == 'system' %}
14
+ {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
15
+ {%- endif %}
16
+ {%- endif %}
17
+ {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
18
+ {%- for message in messages[::-1] %}
19
+ {%- set index = (messages|length - 1) - loop.index0 %}
20
+ {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
21
+ {%- set ns.multi_step_tool = false %}
22
+ {%- set ns.last_query_index = index %}
23
+ {%- endif %}
24
+ {%- endfor %}
25
+ {%- for message in messages %}
26
+ {%- if message.content is string %}
27
+ {%- set content = message.content %}
28
+ {%- else %}
29
+ {%- set content = '' %}
30
+ {%- endif %}
31
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
32
+ {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
33
+ {%- elif message.role == "assistant" %}
34
+ {%- set reasoning_content = '' %}
35
+ {%- if message.reasoning_content is string %}
36
+ {%- set reasoning_content = message.reasoning_content %}
37
+ {%- else %}
38
+ {%- if '</think>' in content %}
39
+ {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
40
+ {%- set content = content.split('</think>')[-1].lstrip('\n') %}
41
+ {%- endif %}
42
+ {%- endif %}
43
+ {%- if loop.index0 > ns.last_query_index %}
44
+ {%- if loop.last or (not loop.last and reasoning_content) %}
45
+ {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
46
+ {%- else %}
47
+ {{- '<|im_start|>' + message.role + '\n' + content }}
48
+ {%- endif %}
49
+ {%- else %}
50
+ {{- '<|im_start|>' + message.role + '\n' + content }}
51
+ {%- endif %}
52
+ {%- if message.tool_calls %}
53
+ {%- for tool_call in message.tool_calls %}
54
+ {%- if (loop.first and content) or (not loop.first) %}
55
+ {{- '\n' }}
56
+ {%- endif %}
57
+ {%- if tool_call.function %}
58
+ {%- set tool_call = tool_call.function %}
59
+ {%- endif %}
60
+ {{- '<tool_call>\n{"name": "' }}
61
+ {{- tool_call.name }}
62
+ {{- '", "arguments": ' }}
63
+ {%- if tool_call.arguments is string %}
64
+ {{- tool_call.arguments }}
65
+ {%- else %}
66
+ {{- tool_call.arguments | tojson }}
67
+ {%- endif %}
68
+ {{- '}\n</tool_call>' }}
69
+ {%- endfor %}
70
+ {%- endif %}
71
+ {{- '<|im_end|>\n' }}
72
+ {%- elif message.role == "tool" %}
73
+ {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
74
+ {{- '<|im_start|>user' }}
75
+ {%- endif %}
76
+ {{- '\n<tool_response>\n' }}
77
+ {{- content }}
78
+ {{- '\n</tool_response>' }}
79
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
80
+ {{- '<|im_end|>\n' }}
81
+ {%- endif %}
82
+ {%- endif %}
83
+ {%- endfor %}
84
+ {%- if add_generation_prompt %}
85
+ {{- '<|im_start|>assistant\n' }}
86
+ {%- if enable_thinking is defined and enable_thinking is false %}
87
+ {{- '<think>\n\n</think>\n\n' }}
88
+ {%- endif %}
89
+ {%- endif %}
Direction/Beaver-Danger/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
Direction/Beaver-Danger/special_tokens_map.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>",
5
+ "<|object_ref_start|>",
6
+ "<|object_ref_end|>",
7
+ "<|box_start|>",
8
+ "<|box_end|>",
9
+ "<|quad_start|>",
10
+ "<|quad_end|>",
11
+ "<|vision_start|>",
12
+ "<|vision_end|>",
13
+ "<|vision_pad|>",
14
+ "<|image_pad|>",
15
+ "<|video_pad|>"
16
+ ],
17
+ "eos_token": {
18
+ "content": "<|im_end|>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ },
24
+ "pad_token": {
25
+ "content": "<|endoftext|>",
26
+ "lstrip": false,
27
+ "normalized": false,
28
+ "rstrip": false,
29
+ "single_word": false
30
+ }
31
+ }
Direction/Beaver-Danger/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
3
+ size 11422654
Direction/Beaver-Danger/tokenizer_config.json ADDED
@@ -0,0 +1,240 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "151643": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "151644": {
14
+ "content": "<|im_start|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "151645": {
22
+ "content": "<|im_end|>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "151646": {
30
+ "content": "<|object_ref_start|>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "151647": {
38
+ "content": "<|object_ref_end|>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "151648": {
46
+ "content": "<|box_start|>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ },
53
+ "151649": {
54
+ "content": "<|box_end|>",
55
+ "lstrip": false,
56
+ "normalized": false,
57
+ "rstrip": false,
58
+ "single_word": false,
59
+ "special": true
60
+ },
61
+ "151650": {
62
+ "content": "<|quad_start|>",
63
+ "lstrip": false,
64
+ "normalized": false,
65
+ "rstrip": false,
66
+ "single_word": false,
67
+ "special": true
68
+ },
69
+ "151651": {
70
+ "content": "<|quad_end|>",
71
+ "lstrip": false,
72
+ "normalized": false,
73
+ "rstrip": false,
74
+ "single_word": false,
75
+ "special": true
76
+ },
77
+ "151652": {
78
+ "content": "<|vision_start|>",
79
+ "lstrip": false,
80
+ "normalized": false,
81
+ "rstrip": false,
82
+ "single_word": false,
83
+ "special": true
84
+ },
85
+ "151653": {
86
+ "content": "<|vision_end|>",
87
+ "lstrip": false,
88
+ "normalized": false,
89
+ "rstrip": false,
90
+ "single_word": false,
91
+ "special": true
92
+ },
93
+ "151654": {
94
+ "content": "<|vision_pad|>",
95
+ "lstrip": false,
96
+ "normalized": false,
97
+ "rstrip": false,
98
+ "single_word": false,
99
+ "special": true
100
+ },
101
+ "151655": {
102
+ "content": "<|image_pad|>",
103
+ "lstrip": false,
104
+ "normalized": false,
105
+ "rstrip": false,
106
+ "single_word": false,
107
+ "special": true
108
+ },
109
+ "151656": {
110
+ "content": "<|video_pad|>",
111
+ "lstrip": false,
112
+ "normalized": false,
113
+ "rstrip": false,
114
+ "single_word": false,
115
+ "special": true
116
+ },
117
+ "151657": {
118
+ "content": "<tool_call>",
119
+ "lstrip": false,
120
+ "normalized": false,
121
+ "rstrip": false,
122
+ "single_word": false,
123
+ "special": false
124
+ },
125
+ "151658": {
126
+ "content": "</tool_call>",
127
+ "lstrip": false,
128
+ "normalized": false,
129
+ "rstrip": false,
130
+ "single_word": false,
131
+ "special": false
132
+ },
133
+ "151659": {
134
+ "content": "<|fim_prefix|>",
135
+ "lstrip": false,
136
+ "normalized": false,
137
+ "rstrip": false,
138
+ "single_word": false,
139
+ "special": false
140
+ },
141
+ "151660": {
142
+ "content": "<|fim_middle|>",
143
+ "lstrip": false,
144
+ "normalized": false,
145
+ "rstrip": false,
146
+ "single_word": false,
147
+ "special": false
148
+ },
149
+ "151661": {
150
+ "content": "<|fim_suffix|>",
151
+ "lstrip": false,
152
+ "normalized": false,
153
+ "rstrip": false,
154
+ "single_word": false,
155
+ "special": false
156
+ },
157
+ "151662": {
158
+ "content": "<|fim_pad|>",
159
+ "lstrip": false,
160
+ "normalized": false,
161
+ "rstrip": false,
162
+ "single_word": false,
163
+ "special": false
164
+ },
165
+ "151663": {
166
+ "content": "<|repo_name|>",
167
+ "lstrip": false,
168
+ "normalized": false,
169
+ "rstrip": false,
170
+ "single_word": false,
171
+ "special": false
172
+ },
173
+ "151664": {
174
+ "content": "<|file_sep|>",
175
+ "lstrip": false,
176
+ "normalized": false,
177
+ "rstrip": false,
178
+ "single_word": false,
179
+ "special": false
180
+ },
181
+ "151665": {
182
+ "content": "<tool_response>",
183
+ "lstrip": false,
184
+ "normalized": false,
185
+ "rstrip": false,
186
+ "single_word": false,
187
+ "special": false
188
+ },
189
+ "151666": {
190
+ "content": "</tool_response>",
191
+ "lstrip": false,
192
+ "normalized": false,
193
+ "rstrip": false,
194
+ "single_word": false,
195
+ "special": false
196
+ },
197
+ "151667": {
198
+ "content": "<think>",
199
+ "lstrip": false,
200
+ "normalized": false,
201
+ "rstrip": false,
202
+ "single_word": false,
203
+ "special": false
204
+ },
205
+ "151668": {
206
+ "content": "</think>",
207
+ "lstrip": false,
208
+ "normalized": false,
209
+ "rstrip": false,
210
+ "single_word": false,
211
+ "special": false
212
+ }
213
+ },
214
+ "additional_special_tokens": [
215
+ "<|im_start|>",
216
+ "<|im_end|>",
217
+ "<|object_ref_start|>",
218
+ "<|object_ref_end|>",
219
+ "<|box_start|>",
220
+ "<|box_end|>",
221
+ "<|quad_start|>",
222
+ "<|quad_end|>",
223
+ "<|vision_start|>",
224
+ "<|vision_end|>",
225
+ "<|vision_pad|>",
226
+ "<|image_pad|>",
227
+ "<|video_pad|>"
228
+ ],
229
+ "bos_token": null,
230
+ "clean_up_tokenization_spaces": false,
231
+ "eos_token": "<|im_end|>",
232
+ "errors": "replace",
233
+ "extra_special_tokens": {},
234
+ "model_max_length": 131072,
235
+ "pad_token": "<|endoftext|>",
236
+ "padding_side": "right",
237
+ "split_special_tokens": false,
238
+ "tokenizer_class": "Qwen2Tokenizer",
239
+ "unk_token": null
240
+ }
Direction/Beaver-Danger/trainer_state.json ADDED
@@ -0,0 +1,2659 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 10.0,
6
+ "eval_steps": 500,
7
+ "global_step": 3750,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.02666666666666667,
14
+ "grad_norm": 1.3260700702667236,
15
+ "learning_rate": 1.2000000000000002e-07,
16
+ "loss": 2.9661,
17
+ "step": 10
18
+ },
19
+ {
20
+ "epoch": 0.05333333333333334,
21
+ "grad_norm": 1.2190521955490112,
22
+ "learning_rate": 2.533333333333333e-07,
23
+ "loss": 2.8546,
24
+ "step": 20
25
+ },
26
+ {
27
+ "epoch": 0.08,
28
+ "grad_norm": 1.063557744026184,
29
+ "learning_rate": 3.8666666666666674e-07,
30
+ "loss": 2.7771,
31
+ "step": 30
32
+ },
33
+ {
34
+ "epoch": 0.10666666666666667,
35
+ "grad_norm": 1.1022443771362305,
36
+ "learning_rate": 5.2e-07,
37
+ "loss": 2.7986,
38
+ "step": 40
39
+ },
40
+ {
41
+ "epoch": 0.13333333333333333,
42
+ "grad_norm": 1.0045348405838013,
43
+ "learning_rate": 6.533333333333334e-07,
44
+ "loss": 2.7848,
45
+ "step": 50
46
+ },
47
+ {
48
+ "epoch": 0.16,
49
+ "grad_norm": 1.1520053148269653,
50
+ "learning_rate": 7.866666666666667e-07,
51
+ "loss": 2.7392,
52
+ "step": 60
53
+ },
54
+ {
55
+ "epoch": 0.18666666666666668,
56
+ "grad_norm": 1.1911686658859253,
57
+ "learning_rate": 9.200000000000001e-07,
58
+ "loss": 2.8294,
59
+ "step": 70
60
+ },
61
+ {
62
+ "epoch": 0.21333333333333335,
63
+ "grad_norm": 0.8869664072990417,
64
+ "learning_rate": 1.0533333333333333e-06,
65
+ "loss": 2.7817,
66
+ "step": 80
67
+ },
68
+ {
69
+ "epoch": 0.24,
70
+ "grad_norm": 1.3061726093292236,
71
+ "learning_rate": 1.1866666666666668e-06,
72
+ "loss": 2.8212,
73
+ "step": 90
74
+ },
75
+ {
76
+ "epoch": 0.26666666666666666,
77
+ "grad_norm": 1.6410006284713745,
78
+ "learning_rate": 1.32e-06,
79
+ "loss": 2.8196,
80
+ "step": 100
81
+ },
82
+ {
83
+ "epoch": 0.29333333333333333,
84
+ "grad_norm": 1.4250684976577759,
85
+ "learning_rate": 1.4533333333333335e-06,
86
+ "loss": 2.6571,
87
+ "step": 110
88
+ },
89
+ {
90
+ "epoch": 0.32,
91
+ "grad_norm": 1.6860215663909912,
92
+ "learning_rate": 1.586666666666667e-06,
93
+ "loss": 2.7758,
94
+ "step": 120
95
+ },
96
+ {
97
+ "epoch": 0.3466666666666667,
98
+ "grad_norm": 1.3881759643554688,
99
+ "learning_rate": 1.72e-06,
100
+ "loss": 2.7617,
101
+ "step": 130
102
+ },
103
+ {
104
+ "epoch": 0.37333333333333335,
105
+ "grad_norm": 1.5089608430862427,
106
+ "learning_rate": 1.8533333333333333e-06,
107
+ "loss": 2.6495,
108
+ "step": 140
109
+ },
110
+ {
111
+ "epoch": 0.4,
112
+ "grad_norm": 1.2898715734481812,
113
+ "learning_rate": 1.9866666666666666e-06,
114
+ "loss": 2.7944,
115
+ "step": 150
116
+ },
117
+ {
118
+ "epoch": 0.4266666666666667,
119
+ "grad_norm": 2.510946273803711,
120
+ "learning_rate": 2.12e-06,
121
+ "loss": 2.7703,
122
+ "step": 160
123
+ },
124
+ {
125
+ "epoch": 0.4533333333333333,
126
+ "grad_norm": 1.4257193803787231,
127
+ "learning_rate": 2.2533333333333335e-06,
128
+ "loss": 2.6653,
129
+ "step": 170
130
+ },
131
+ {
132
+ "epoch": 0.48,
133
+ "grad_norm": 1.9228178262710571,
134
+ "learning_rate": 2.386666666666667e-06,
135
+ "loss": 2.6569,
136
+ "step": 180
137
+ },
138
+ {
139
+ "epoch": 0.5066666666666667,
140
+ "grad_norm": 1.9167159795761108,
141
+ "learning_rate": 2.52e-06,
142
+ "loss": 2.5694,
143
+ "step": 190
144
+ },
145
+ {
146
+ "epoch": 0.5333333333333333,
147
+ "grad_norm": 1.9402084350585938,
148
+ "learning_rate": 2.6533333333333335e-06,
149
+ "loss": 2.4804,
150
+ "step": 200
151
+ },
152
+ {
153
+ "epoch": 0.56,
154
+ "grad_norm": 1.3673012256622314,
155
+ "learning_rate": 2.786666666666667e-06,
156
+ "loss": 2.3965,
157
+ "step": 210
158
+ },
159
+ {
160
+ "epoch": 0.5866666666666667,
161
+ "grad_norm": 1.1642200946807861,
162
+ "learning_rate": 2.92e-06,
163
+ "loss": 2.4015,
164
+ "step": 220
165
+ },
166
+ {
167
+ "epoch": 0.6133333333333333,
168
+ "grad_norm": 0.8972470760345459,
169
+ "learning_rate": 3.053333333333334e-06,
170
+ "loss": 2.2293,
171
+ "step": 230
172
+ },
173
+ {
174
+ "epoch": 0.64,
175
+ "grad_norm": 1.0226929187774658,
176
+ "learning_rate": 3.186666666666667e-06,
177
+ "loss": 2.2138,
178
+ "step": 240
179
+ },
180
+ {
181
+ "epoch": 0.6666666666666666,
182
+ "grad_norm": 1.28902006149292,
183
+ "learning_rate": 3.3200000000000004e-06,
184
+ "loss": 2.1027,
185
+ "step": 250
186
+ },
187
+ {
188
+ "epoch": 0.6933333333333334,
189
+ "grad_norm": 1.0202113389968872,
190
+ "learning_rate": 3.4533333333333334e-06,
191
+ "loss": 2.0698,
192
+ "step": 260
193
+ },
194
+ {
195
+ "epoch": 0.72,
196
+ "grad_norm": 0.9459338188171387,
197
+ "learning_rate": 3.5866666666666673e-06,
198
+ "loss": 2.0861,
199
+ "step": 270
200
+ },
201
+ {
202
+ "epoch": 0.7466666666666667,
203
+ "grad_norm": 1.0297719240188599,
204
+ "learning_rate": 3.7200000000000004e-06,
205
+ "loss": 2.0712,
206
+ "step": 280
207
+ },
208
+ {
209
+ "epoch": 0.7733333333333333,
210
+ "grad_norm": 1.0611679553985596,
211
+ "learning_rate": 3.853333333333334e-06,
212
+ "loss": 1.9712,
213
+ "step": 290
214
+ },
215
+ {
216
+ "epoch": 0.8,
217
+ "grad_norm": 0.9117859601974487,
218
+ "learning_rate": 3.986666666666667e-06,
219
+ "loss": 2.0212,
220
+ "step": 300
221
+ },
222
+ {
223
+ "epoch": 0.8266666666666667,
224
+ "grad_norm": 0.820168673992157,
225
+ "learning_rate": 4.12e-06,
226
+ "loss": 1.9746,
227
+ "step": 310
228
+ },
229
+ {
230
+ "epoch": 0.8533333333333334,
231
+ "grad_norm": 0.7669106125831604,
232
+ "learning_rate": 4.253333333333334e-06,
233
+ "loss": 1.9602,
234
+ "step": 320
235
+ },
236
+ {
237
+ "epoch": 0.88,
238
+ "grad_norm": 0.7456678748130798,
239
+ "learning_rate": 4.3866666666666665e-06,
240
+ "loss": 1.9342,
241
+ "step": 330
242
+ },
243
+ {
244
+ "epoch": 0.9066666666666666,
245
+ "grad_norm": 0.8794134855270386,
246
+ "learning_rate": 4.520000000000001e-06,
247
+ "loss": 1.9663,
248
+ "step": 340
249
+ },
250
+ {
251
+ "epoch": 0.9333333333333333,
252
+ "grad_norm": 0.6996933221817017,
253
+ "learning_rate": 4.653333333333333e-06,
254
+ "loss": 1.9244,
255
+ "step": 350
256
+ },
257
+ {
258
+ "epoch": 0.96,
259
+ "grad_norm": 1.4994454383850098,
260
+ "learning_rate": 4.786666666666667e-06,
261
+ "loss": 1.9133,
262
+ "step": 360
263
+ },
264
+ {
265
+ "epoch": 0.9866666666666667,
266
+ "grad_norm": 0.8297287225723267,
267
+ "learning_rate": 4.92e-06,
268
+ "loss": 1.9561,
269
+ "step": 370
270
+ },
271
+ {
272
+ "epoch": 1.0133333333333334,
273
+ "grad_norm": 0.793429970741272,
274
+ "learning_rate": 4.999982670673473e-06,
275
+ "loss": 1.8335,
276
+ "step": 380
277
+ },
278
+ {
279
+ "epoch": 1.04,
280
+ "grad_norm": 1.2577004432678223,
281
+ "learning_rate": 4.999787718509086e-06,
282
+ "loss": 1.9429,
283
+ "step": 390
284
+ },
285
+ {
286
+ "epoch": 1.0666666666666667,
287
+ "grad_norm": 0.8015560507774353,
288
+ "learning_rate": 4.999376169470306e-06,
289
+ "loss": 1.9304,
290
+ "step": 400
291
+ },
292
+ {
293
+ "epoch": 1.0933333333333333,
294
+ "grad_norm": 0.6889002323150635,
295
+ "learning_rate": 4.998748059216254e-06,
296
+ "loss": 1.7845,
297
+ "step": 410
298
+ },
299
+ {
300
+ "epoch": 1.12,
301
+ "grad_norm": 0.9721826314926147,
302
+ "learning_rate": 4.997903442170241e-06,
303
+ "loss": 1.8076,
304
+ "step": 420
305
+ },
306
+ {
307
+ "epoch": 1.1466666666666667,
308
+ "grad_norm": 1.0830353498458862,
309
+ "learning_rate": 4.996842391515045e-06,
310
+ "loss": 1.8498,
311
+ "step": 430
312
+ },
313
+ {
314
+ "epoch": 1.1733333333333333,
315
+ "grad_norm": 0.6819325089454651,
316
+ "learning_rate": 4.995564999186572e-06,
317
+ "loss": 1.8069,
318
+ "step": 440
319
+ },
320
+ {
321
+ "epoch": 1.2,
322
+ "grad_norm": 0.8205446004867554,
323
+ "learning_rate": 4.994071375865898e-06,
324
+ "loss": 1.8426,
325
+ "step": 450
326
+ },
327
+ {
328
+ "epoch": 1.2266666666666666,
329
+ "grad_norm": 0.7085703611373901,
330
+ "learning_rate": 4.992361650969668e-06,
331
+ "loss": 1.7295,
332
+ "step": 460
333
+ },
334
+ {
335
+ "epoch": 1.2533333333333334,
336
+ "grad_norm": 0.7688453197479248,
337
+ "learning_rate": 4.990435972638888e-06,
338
+ "loss": 1.8634,
339
+ "step": 470
340
+ },
341
+ {
342
+ "epoch": 1.28,
343
+ "grad_norm": 0.7346873879432678,
344
+ "learning_rate": 4.988294507726089e-06,
345
+ "loss": 1.7841,
346
+ "step": 480
347
+ },
348
+ {
349
+ "epoch": 1.3066666666666666,
350
+ "grad_norm": 0.6709712743759155,
351
+ "learning_rate": 4.98593744178087e-06,
352
+ "loss": 1.7151,
353
+ "step": 490
354
+ },
355
+ {
356
+ "epoch": 1.3333333333333333,
357
+ "grad_norm": 0.7021077871322632,
358
+ "learning_rate": 4.983364979033819e-06,
359
+ "loss": 1.7789,
360
+ "step": 500
361
+ },
362
+ {
363
+ "epoch": 1.3599999999999999,
364
+ "grad_norm": 0.6195208430290222,
365
+ "learning_rate": 4.980577342378818e-06,
366
+ "loss": 1.8095,
367
+ "step": 510
368
+ },
369
+ {
370
+ "epoch": 1.3866666666666667,
371
+ "grad_norm": 0.8497361540794373,
372
+ "learning_rate": 4.977574773353732e-06,
373
+ "loss": 1.7106,
374
+ "step": 520
375
+ },
376
+ {
377
+ "epoch": 1.4133333333333333,
378
+ "grad_norm": 0.9590965509414673,
379
+ "learning_rate": 4.974357532119478e-06,
380
+ "loss": 1.7598,
381
+ "step": 530
382
+ },
383
+ {
384
+ "epoch": 1.44,
385
+ "grad_norm": 0.6314051151275635,
386
+ "learning_rate": 4.970925897437484e-06,
387
+ "loss": 1.7866,
388
+ "step": 540
389
+ },
390
+ {
391
+ "epoch": 1.4666666666666668,
392
+ "grad_norm": 0.6002180576324463,
393
+ "learning_rate": 4.967280166645538e-06,
394
+ "loss": 1.7957,
395
+ "step": 550
396
+ },
397
+ {
398
+ "epoch": 1.4933333333333334,
399
+ "grad_norm": 0.9273757934570312,
400
+ "learning_rate": 4.9634206556320186e-06,
401
+ "loss": 1.7368,
402
+ "step": 560
403
+ },
404
+ {
405
+ "epoch": 1.52,
406
+ "grad_norm": 0.9748147130012512,
407
+ "learning_rate": 4.959347698808532e-06,
408
+ "loss": 1.7901,
409
+ "step": 570
410
+ },
411
+ {
412
+ "epoch": 1.5466666666666666,
413
+ "grad_norm": 0.7918932437896729,
414
+ "learning_rate": 4.95506164908093e-06,
415
+ "loss": 1.7963,
416
+ "step": 580
417
+ },
418
+ {
419
+ "epoch": 1.5733333333333333,
420
+ "grad_norm": 0.823905348777771,
421
+ "learning_rate": 4.9505628778187365e-06,
422
+ "loss": 1.8262,
423
+ "step": 590
424
+ },
425
+ {
426
+ "epoch": 1.6,
427
+ "grad_norm": 0.7708048820495605,
428
+ "learning_rate": 4.94585177482297e-06,
429
+ "loss": 1.784,
430
+ "step": 600
431
+ },
432
+ {
433
+ "epoch": 1.6266666666666667,
434
+ "grad_norm": 0.6546101570129395,
435
+ "learning_rate": 4.940928748292363e-06,
436
+ "loss": 1.7299,
437
+ "step": 610
438
+ },
439
+ {
440
+ "epoch": 1.6533333333333333,
441
+ "grad_norm": 0.9508903622627258,
442
+ "learning_rate": 4.9357942247879995e-06,
443
+ "loss": 1.7814,
444
+ "step": 620
445
+ },
446
+ {
447
+ "epoch": 1.6800000000000002,
448
+ "grad_norm": 0.8177071213722229,
449
+ "learning_rate": 4.930448649196356e-06,
450
+ "loss": 1.7693,
451
+ "step": 630
452
+ },
453
+ {
454
+ "epoch": 1.7066666666666666,
455
+ "grad_norm": 0.8351238369941711,
456
+ "learning_rate": 4.924892484690744e-06,
457
+ "loss": 1.7546,
458
+ "step": 640
459
+ },
460
+ {
461
+ "epoch": 1.7333333333333334,
462
+ "grad_norm": 0.6392200589179993,
463
+ "learning_rate": 4.91912621269119e-06,
464
+ "loss": 1.7813,
465
+ "step": 650
466
+ },
467
+ {
468
+ "epoch": 1.76,
469
+ "grad_norm": 0.7682125568389893,
470
+ "learning_rate": 4.913150332822716e-06,
471
+ "loss": 1.705,
472
+ "step": 660
473
+ },
474
+ {
475
+ "epoch": 1.7866666666666666,
476
+ "grad_norm": 0.853183925151825,
477
+ "learning_rate": 4.906965362872048e-06,
478
+ "loss": 1.7138,
479
+ "step": 670
480
+ },
481
+ {
482
+ "epoch": 1.8133333333333335,
483
+ "grad_norm": 0.6856978535652161,
484
+ "learning_rate": 4.9005718387427546e-06,
485
+ "loss": 1.7742,
486
+ "step": 680
487
+ },
488
+ {
489
+ "epoch": 1.8399999999999999,
490
+ "grad_norm": 0.7499570846557617,
491
+ "learning_rate": 4.893970314408813e-06,
492
+ "loss": 1.8262,
493
+ "step": 690
494
+ },
495
+ {
496
+ "epoch": 1.8666666666666667,
497
+ "grad_norm": 0.9084373712539673,
498
+ "learning_rate": 4.887161361866608e-06,
499
+ "loss": 1.7991,
500
+ "step": 700
501
+ },
502
+ {
503
+ "epoch": 1.8933333333333333,
504
+ "grad_norm": 0.7706170082092285,
505
+ "learning_rate": 4.880145571085369e-06,
506
+ "loss": 1.7892,
507
+ "step": 710
508
+ },
509
+ {
510
+ "epoch": 1.92,
511
+ "grad_norm": 0.8223916292190552,
512
+ "learning_rate": 4.872923549956058e-06,
513
+ "loss": 1.7989,
514
+ "step": 720
515
+ },
516
+ {
517
+ "epoch": 1.9466666666666668,
518
+ "grad_norm": 0.8382287621498108,
519
+ "learning_rate": 4.86549592423869e-06,
520
+ "loss": 1.8062,
521
+ "step": 730
522
+ },
523
+ {
524
+ "epoch": 1.9733333333333334,
525
+ "grad_norm": 0.562559187412262,
526
+ "learning_rate": 4.857863337508119e-06,
527
+ "loss": 1.7391,
528
+ "step": 740
529
+ },
530
+ {
531
+ "epoch": 2.0,
532
+ "grad_norm": 0.9999620914459229,
533
+ "learning_rate": 4.850026451098271e-06,
534
+ "loss": 1.7954,
535
+ "step": 750
536
+ },
537
+ {
538
+ "epoch": 2.026666666666667,
539
+ "grad_norm": 0.7311544418334961,
540
+ "learning_rate": 4.841985944044845e-06,
541
+ "loss": 1.7463,
542
+ "step": 760
543
+ },
544
+ {
545
+ "epoch": 2.0533333333333332,
546
+ "grad_norm": 0.8479844331741333,
547
+ "learning_rate": 4.833742513026478e-06,
548
+ "loss": 1.7205,
549
+ "step": 770
550
+ },
551
+ {
552
+ "epoch": 2.08,
553
+ "grad_norm": 0.9184486865997314,
554
+ "learning_rate": 4.825296872304377e-06,
555
+ "loss": 1.7573,
556
+ "step": 780
557
+ },
558
+ {
559
+ "epoch": 2.1066666666666665,
560
+ "grad_norm": 0.8509571552276611,
561
+ "learning_rate": 4.816649753660431e-06,
562
+ "loss": 1.7615,
563
+ "step": 790
564
+ },
565
+ {
566
+ "epoch": 2.1333333333333333,
567
+ "grad_norm": 0.6607502698898315,
568
+ "learning_rate": 4.807801906333809e-06,
569
+ "loss": 1.7398,
570
+ "step": 800
571
+ },
572
+ {
573
+ "epoch": 2.16,
574
+ "grad_norm": 0.8238988518714905,
575
+ "learning_rate": 4.7987540969560385e-06,
576
+ "loss": 1.7306,
577
+ "step": 810
578
+ },
579
+ {
580
+ "epoch": 2.1866666666666665,
581
+ "grad_norm": 0.868171215057373,
582
+ "learning_rate": 4.789507109484579e-06,
583
+ "loss": 1.7441,
584
+ "step": 820
585
+ },
586
+ {
587
+ "epoch": 2.2133333333333334,
588
+ "grad_norm": 0.7437669038772583,
589
+ "learning_rate": 4.7800617451348974e-06,
590
+ "loss": 1.7433,
591
+ "step": 830
592
+ },
593
+ {
594
+ "epoch": 2.24,
595
+ "grad_norm": 0.7135257720947266,
596
+ "learning_rate": 4.770418822311046e-06,
597
+ "loss": 1.789,
598
+ "step": 840
599
+ },
600
+ {
601
+ "epoch": 2.2666666666666666,
602
+ "grad_norm": 0.8468518853187561,
603
+ "learning_rate": 4.760579176534747e-06,
604
+ "loss": 1.7478,
605
+ "step": 850
606
+ },
607
+ {
608
+ "epoch": 2.2933333333333334,
609
+ "grad_norm": 1.2122632265090942,
610
+ "learning_rate": 4.750543660373004e-06,
611
+ "loss": 1.6655,
612
+ "step": 860
613
+ },
614
+ {
615
+ "epoch": 2.32,
616
+ "grad_norm": 0.7517653107643127,
617
+ "learning_rate": 4.7403131433642226e-06,
618
+ "loss": 1.6733,
619
+ "step": 870
620
+ },
621
+ {
622
+ "epoch": 2.3466666666666667,
623
+ "grad_norm": 0.9318462014198303,
624
+ "learning_rate": 4.729888511942877e-06,
625
+ "loss": 1.7519,
626
+ "step": 880
627
+ },
628
+ {
629
+ "epoch": 2.3733333333333335,
630
+ "grad_norm": 0.854913592338562,
631
+ "learning_rate": 4.719270669362699e-06,
632
+ "loss": 1.7217,
633
+ "step": 890
634
+ },
635
+ {
636
+ "epoch": 2.4,
637
+ "grad_norm": 0.67042475938797,
638
+ "learning_rate": 4.708460535618411e-06,
639
+ "loss": 1.7709,
640
+ "step": 900
641
+ },
642
+ {
643
+ "epoch": 2.4266666666666667,
644
+ "grad_norm": 0.7077845931053162,
645
+ "learning_rate": 4.697459047366022e-06,
646
+ "loss": 1.7217,
647
+ "step": 910
648
+ },
649
+ {
650
+ "epoch": 2.453333333333333,
651
+ "grad_norm": 0.7887906432151794,
652
+ "learning_rate": 4.68626715784166e-06,
653
+ "loss": 1.7028,
654
+ "step": 920
655
+ },
656
+ {
657
+ "epoch": 2.48,
658
+ "grad_norm": 0.8714291453361511,
659
+ "learning_rate": 4.674885836778983e-06,
660
+ "loss": 1.824,
661
+ "step": 930
662
+ },
663
+ {
664
+ "epoch": 2.506666666666667,
665
+ "grad_norm": 0.8725156784057617,
666
+ "learning_rate": 4.6633160703251556e-06,
667
+ "loss": 1.7337,
668
+ "step": 940
669
+ },
670
+ {
671
+ "epoch": 2.533333333333333,
672
+ "grad_norm": 0.6795626282691956,
673
+ "learning_rate": 4.6515588609554006e-06,
674
+ "loss": 1.7776,
675
+ "step": 950
676
+ },
677
+ {
678
+ "epoch": 2.56,
679
+ "grad_norm": 0.8653692603111267,
680
+ "learning_rate": 4.639615227386141e-06,
681
+ "loss": 1.6206,
682
+ "step": 960
683
+ },
684
+ {
685
+ "epoch": 2.586666666666667,
686
+ "grad_norm": 0.7805237770080566,
687
+ "learning_rate": 4.62748620448673e-06,
688
+ "loss": 1.7503,
689
+ "step": 970
690
+ },
691
+ {
692
+ "epoch": 2.6133333333333333,
693
+ "grad_norm": 0.7651466727256775,
694
+ "learning_rate": 4.615172843189785e-06,
695
+ "loss": 1.7778,
696
+ "step": 980
697
+ },
698
+ {
699
+ "epoch": 2.64,
700
+ "grad_norm": 0.8041864633560181,
701
+ "learning_rate": 4.602676210400126e-06,
702
+ "loss": 1.6354,
703
+ "step": 990
704
+ },
705
+ {
706
+ "epoch": 2.6666666666666665,
707
+ "grad_norm": 0.7719329595565796,
708
+ "learning_rate": 4.589997388902339e-06,
709
+ "loss": 1.7719,
710
+ "step": 1000
711
+ },
712
+ {
713
+ "epoch": 2.6933333333333334,
714
+ "grad_norm": 0.9812129735946655,
715
+ "learning_rate": 4.577137477266948e-06,
716
+ "loss": 1.7822,
717
+ "step": 1010
718
+ },
719
+ {
720
+ "epoch": 2.7199999999999998,
721
+ "grad_norm": 0.7337241172790527,
722
+ "learning_rate": 4.564097589755233e-06,
723
+ "loss": 1.7204,
724
+ "step": 1020
725
+ },
726
+ {
727
+ "epoch": 2.7466666666666666,
728
+ "grad_norm": 0.5740780234336853,
729
+ "learning_rate": 4.550878856222684e-06,
730
+ "loss": 1.7386,
731
+ "step": 1030
732
+ },
733
+ {
734
+ "epoch": 2.7733333333333334,
735
+ "grad_norm": 0.7582064270973206,
736
+ "learning_rate": 4.537482422021105e-06,
737
+ "loss": 1.7177,
738
+ "step": 1040
739
+ },
740
+ {
741
+ "epoch": 2.8,
742
+ "grad_norm": 0.775303304195404,
743
+ "learning_rate": 4.523909447899365e-06,
744
+ "loss": 1.7284,
745
+ "step": 1050
746
+ },
747
+ {
748
+ "epoch": 2.8266666666666667,
749
+ "grad_norm": 0.7809900641441345,
750
+ "learning_rate": 4.510161109902837e-06,
751
+ "loss": 1.7085,
752
+ "step": 1060
753
+ },
754
+ {
755
+ "epoch": 2.8533333333333335,
756
+ "grad_norm": 0.8396899700164795,
757
+ "learning_rate": 4.496238599271485e-06,
758
+ "loss": 1.684,
759
+ "step": 1070
760
+ },
761
+ {
762
+ "epoch": 2.88,
763
+ "grad_norm": 0.7145466208457947,
764
+ "learning_rate": 4.482143122336658e-06,
765
+ "loss": 1.7753,
766
+ "step": 1080
767
+ },
768
+ {
769
+ "epoch": 2.9066666666666667,
770
+ "grad_norm": 0.7297652959823608,
771
+ "learning_rate": 4.467875900416558e-06,
772
+ "loss": 1.6807,
773
+ "step": 1090
774
+ },
775
+ {
776
+ "epoch": 2.9333333333333336,
777
+ "grad_norm": 0.7068011164665222,
778
+ "learning_rate": 4.4534381697104255e-06,
779
+ "loss": 1.7068,
780
+ "step": 1100
781
+ },
782
+ {
783
+ "epoch": 2.96,
784
+ "grad_norm": 0.7846283316612244,
785
+ "learning_rate": 4.438831181191422e-06,
786
+ "loss": 1.6906,
787
+ "step": 1110
788
+ },
789
+ {
790
+ "epoch": 2.986666666666667,
791
+ "grad_norm": 0.8811623454093933,
792
+ "learning_rate": 4.424056200498237e-06,
793
+ "loss": 1.6248,
794
+ "step": 1120
795
+ },
796
+ {
797
+ "epoch": 3.013333333333333,
798
+ "grad_norm": 0.8921287059783936,
799
+ "learning_rate": 4.409114507825431e-06,
800
+ "loss": 1.6849,
801
+ "step": 1130
802
+ },
803
+ {
804
+ "epoch": 3.04,
805
+ "grad_norm": 0.6005886793136597,
806
+ "learning_rate": 4.394007397812509e-06,
807
+ "loss": 1.7756,
808
+ "step": 1140
809
+ },
810
+ {
811
+ "epoch": 3.066666666666667,
812
+ "grad_norm": 0.8570132851600647,
813
+ "learning_rate": 4.3787361794317405e-06,
814
+ "loss": 1.6584,
815
+ "step": 1150
816
+ },
817
+ {
818
+ "epoch": 3.0933333333333333,
819
+ "grad_norm": 0.7680262923240662,
820
+ "learning_rate": 4.363302175874751e-06,
821
+ "loss": 1.7428,
822
+ "step": 1160
823
+ },
824
+ {
825
+ "epoch": 3.12,
826
+ "grad_norm": 0.9048510789871216,
827
+ "learning_rate": 4.347706724437865e-06,
828
+ "loss": 1.6959,
829
+ "step": 1170
830
+ },
831
+ {
832
+ "epoch": 3.1466666666666665,
833
+ "grad_norm": 0.7438698410987854,
834
+ "learning_rate": 4.33195117640624e-06,
835
+ "loss": 1.7442,
836
+ "step": 1180
837
+ },
838
+ {
839
+ "epoch": 3.1733333333333333,
840
+ "grad_norm": 0.7802926301956177,
841
+ "learning_rate": 4.316036896936774e-06,
842
+ "loss": 1.6798,
843
+ "step": 1190
844
+ },
845
+ {
846
+ "epoch": 3.2,
847
+ "grad_norm": 0.8764957785606384,
848
+ "learning_rate": 4.299965264939834e-06,
849
+ "loss": 1.7208,
850
+ "step": 1200
851
+ },
852
+ {
853
+ "epoch": 3.2266666666666666,
854
+ "grad_norm": 0.8330620527267456,
855
+ "learning_rate": 4.283737672959766e-06,
856
+ "loss": 1.6817,
857
+ "step": 1210
858
+ },
859
+ {
860
+ "epoch": 3.2533333333333334,
861
+ "grad_norm": 0.905133068561554,
862
+ "learning_rate": 4.267355527054243e-06,
863
+ "loss": 1.7485,
864
+ "step": 1220
865
+ },
866
+ {
867
+ "epoch": 3.2800000000000002,
868
+ "grad_norm": 0.6527189612388611,
869
+ "learning_rate": 4.250820246672433e-06,
870
+ "loss": 1.7212,
871
+ "step": 1230
872
+ },
873
+ {
874
+ "epoch": 3.3066666666666666,
875
+ "grad_norm": 0.7526225447654724,
876
+ "learning_rate": 4.234133264532012e-06,
877
+ "loss": 1.7012,
878
+ "step": 1240
879
+ },
880
+ {
881
+ "epoch": 3.3333333333333335,
882
+ "grad_norm": 0.7123927474021912,
883
+ "learning_rate": 4.217296026495022e-06,
884
+ "loss": 1.6295,
885
+ "step": 1250
886
+ },
887
+ {
888
+ "epoch": 3.36,
889
+ "grad_norm": 0.8093245625495911,
890
+ "learning_rate": 4.200309991442591e-06,
891
+ "loss": 1.7663,
892
+ "step": 1260
893
+ },
894
+ {
895
+ "epoch": 3.3866666666666667,
896
+ "grad_norm": 1.3336246013641357,
897
+ "learning_rate": 4.1831766311485345e-06,
898
+ "loss": 1.717,
899
+ "step": 1270
900
+ },
901
+ {
902
+ "epoch": 3.413333333333333,
903
+ "grad_norm": 0.7733551263809204,
904
+ "learning_rate": 4.165897430151822e-06,
905
+ "loss": 1.725,
906
+ "step": 1280
907
+ },
908
+ {
909
+ "epoch": 3.44,
910
+ "grad_norm": 0.8533732295036316,
911
+ "learning_rate": 4.148473885627952e-06,
912
+ "loss": 1.7301,
913
+ "step": 1290
914
+ },
915
+ {
916
+ "epoch": 3.466666666666667,
917
+ "grad_norm": 0.9067566990852356,
918
+ "learning_rate": 4.130907507259233e-06,
919
+ "loss": 1.7135,
920
+ "step": 1300
921
+ },
922
+ {
923
+ "epoch": 3.493333333333333,
924
+ "grad_norm": 0.7603811621665955,
925
+ "learning_rate": 4.113199817103964e-06,
926
+ "loss": 1.7212,
927
+ "step": 1310
928
+ },
929
+ {
930
+ "epoch": 3.52,
931
+ "grad_norm": 0.8485473990440369,
932
+ "learning_rate": 4.095352349464564e-06,
933
+ "loss": 1.6639,
934
+ "step": 1320
935
+ },
936
+ {
937
+ "epoch": 3.546666666666667,
938
+ "grad_norm": 0.7045131921768188,
939
+ "learning_rate": 4.077366650754624e-06,
940
+ "loss": 1.7154,
941
+ "step": 1330
942
+ },
943
+ {
944
+ "epoch": 3.5733333333333333,
945
+ "grad_norm": 1.1325947046279907,
946
+ "learning_rate": 4.059244279364923e-06,
947
+ "loss": 1.7172,
948
+ "step": 1340
949
+ },
950
+ {
951
+ "epoch": 3.6,
952
+ "grad_norm": 0.9101923704147339,
953
+ "learning_rate": 4.040986805528392e-06,
954
+ "loss": 1.7554,
955
+ "step": 1350
956
+ },
957
+ {
958
+ "epoch": 3.626666666666667,
959
+ "grad_norm": 0.758923351764679,
960
+ "learning_rate": 4.022595811184064e-06,
961
+ "loss": 1.6887,
962
+ "step": 1360
963
+ },
964
+ {
965
+ "epoch": 3.6533333333333333,
966
+ "grad_norm": 0.8347360491752625,
967
+ "learning_rate": 4.004072889840006e-06,
968
+ "loss": 1.6517,
969
+ "step": 1370
970
+ },
971
+ {
972
+ "epoch": 3.68,
973
+ "grad_norm": 0.678141713142395,
974
+ "learning_rate": 3.985419646435244e-06,
975
+ "loss": 1.6396,
976
+ "step": 1380
977
+ },
978
+ {
979
+ "epoch": 3.7066666666666666,
980
+ "grad_norm": 0.6728235483169556,
981
+ "learning_rate": 3.966637697200704e-06,
982
+ "loss": 1.6285,
983
+ "step": 1390
984
+ },
985
+ {
986
+ "epoch": 3.7333333333333334,
987
+ "grad_norm": 0.882037878036499,
988
+ "learning_rate": 3.94772866951917e-06,
989
+ "loss": 1.6916,
990
+ "step": 1400
991
+ },
992
+ {
993
+ "epoch": 3.76,
994
+ "grad_norm": 0.8103038668632507,
995
+ "learning_rate": 3.928694201784282e-06,
996
+ "loss": 1.7442,
997
+ "step": 1410
998
+ },
999
+ {
1000
+ "epoch": 3.7866666666666666,
1001
+ "grad_norm": 0.8916019201278687,
1002
+ "learning_rate": 3.909535943258567e-06,
1003
+ "loss": 1.7152,
1004
+ "step": 1420
1005
+ },
1006
+ {
1007
+ "epoch": 3.8133333333333335,
1008
+ "grad_norm": 0.8124565482139587,
1009
+ "learning_rate": 3.890255553930548e-06,
1010
+ "loss": 1.584,
1011
+ "step": 1430
1012
+ },
1013
+ {
1014
+ "epoch": 3.84,
1015
+ "grad_norm": 1.175717830657959,
1016
+ "learning_rate": 3.870854704370902e-06,
1017
+ "loss": 1.6622,
1018
+ "step": 1440
1019
+ },
1020
+ {
1021
+ "epoch": 3.8666666666666667,
1022
+ "grad_norm": 0.7688944339752197,
1023
+ "learning_rate": 3.851335075587717e-06,
1024
+ "loss": 1.6617,
1025
+ "step": 1450
1026
+ },
1027
+ {
1028
+ "epoch": 3.8933333333333335,
1029
+ "grad_norm": 0.8198382258415222,
1030
+ "learning_rate": 3.831698358880843e-06,
1031
+ "loss": 1.7615,
1032
+ "step": 1460
1033
+ },
1034
+ {
1035
+ "epoch": 3.92,
1036
+ "grad_norm": 0.9463858008384705,
1037
+ "learning_rate": 3.8119462556953358e-06,
1038
+ "loss": 1.7056,
1039
+ "step": 1470
1040
+ },
1041
+ {
1042
+ "epoch": 3.9466666666666668,
1043
+ "grad_norm": 0.860659658908844,
1044
+ "learning_rate": 3.7920804774740427e-06,
1045
+ "loss": 1.7146,
1046
+ "step": 1480
1047
+ },
1048
+ {
1049
+ "epoch": 3.9733333333333336,
1050
+ "grad_norm": 0.6901930570602417,
1051
+ "learning_rate": 3.772102745509313e-06,
1052
+ "loss": 1.6673,
1053
+ "step": 1490
1054
+ },
1055
+ {
1056
+ "epoch": 4.0,
1057
+ "grad_norm": 0.8208654522895813,
1058
+ "learning_rate": 3.75201479079385e-06,
1059
+ "loss": 1.6727,
1060
+ "step": 1500
1061
+ },
1062
+ {
1063
+ "epoch": 4.026666666666666,
1064
+ "grad_norm": 0.8625465035438538,
1065
+ "learning_rate": 3.731818353870729e-06,
1066
+ "loss": 1.7461,
1067
+ "step": 1510
1068
+ },
1069
+ {
1070
+ "epoch": 4.053333333333334,
1071
+ "grad_norm": 0.9363060593605042,
1072
+ "learning_rate": 3.7115151846825874e-06,
1073
+ "loss": 1.6987,
1074
+ "step": 1520
1075
+ },
1076
+ {
1077
+ "epoch": 4.08,
1078
+ "grad_norm": 0.85496985912323,
1079
+ "learning_rate": 3.6911070424199967e-06,
1080
+ "loss": 1.7011,
1081
+ "step": 1530
1082
+ },
1083
+ {
1084
+ "epoch": 4.1066666666666665,
1085
+ "grad_norm": 0.7028411626815796,
1086
+ "learning_rate": 3.6705956953690364e-06,
1087
+ "loss": 1.7364,
1088
+ "step": 1540
1089
+ },
1090
+ {
1091
+ "epoch": 4.133333333333334,
1092
+ "grad_norm": 0.7788967490196228,
1093
+ "learning_rate": 3.649982920758082e-06,
1094
+ "loss": 1.6497,
1095
+ "step": 1550
1096
+ },
1097
+ {
1098
+ "epoch": 4.16,
1099
+ "grad_norm": 0.7477676272392273,
1100
+ "learning_rate": 3.6292705046038077e-06,
1101
+ "loss": 1.6234,
1102
+ "step": 1560
1103
+ },
1104
+ {
1105
+ "epoch": 4.1866666666666665,
1106
+ "grad_norm": 0.9469152092933655,
1107
+ "learning_rate": 3.608460241556443e-06,
1108
+ "loss": 1.7088,
1109
+ "step": 1570
1110
+ },
1111
+ {
1112
+ "epoch": 4.213333333333333,
1113
+ "grad_norm": 0.71943598985672,
1114
+ "learning_rate": 3.5875539347442694e-06,
1115
+ "loss": 1.6717,
1116
+ "step": 1580
1117
+ },
1118
+ {
1119
+ "epoch": 4.24,
1120
+ "grad_norm": 1.0844371318817139,
1121
+ "learning_rate": 3.5665533956173857e-06,
1122
+ "loss": 1.6755,
1123
+ "step": 1590
1124
+ },
1125
+ {
1126
+ "epoch": 4.266666666666667,
1127
+ "grad_norm": 0.6315621137619019,
1128
+ "learning_rate": 3.5454604437907535e-06,
1129
+ "loss": 1.7006,
1130
+ "step": 1600
1131
+ },
1132
+ {
1133
+ "epoch": 4.293333333333333,
1134
+ "grad_norm": 1.314296007156372,
1135
+ "learning_rate": 3.5242769068865375e-06,
1136
+ "loss": 1.6445,
1137
+ "step": 1610
1138
+ },
1139
+ {
1140
+ "epoch": 4.32,
1141
+ "grad_norm": 0.684222400188446,
1142
+ "learning_rate": 3.503004620375744e-06,
1143
+ "loss": 1.7615,
1144
+ "step": 1620
1145
+ },
1146
+ {
1147
+ "epoch": 4.346666666666667,
1148
+ "grad_norm": 0.9206071496009827,
1149
+ "learning_rate": 3.481645427419188e-06,
1150
+ "loss": 1.6997,
1151
+ "step": 1630
1152
+ },
1153
+ {
1154
+ "epoch": 4.373333333333333,
1155
+ "grad_norm": 0.8316521048545837,
1156
+ "learning_rate": 3.460201178707791e-06,
1157
+ "loss": 1.6902,
1158
+ "step": 1640
1159
+ },
1160
+ {
1161
+ "epoch": 4.4,
1162
+ "grad_norm": 0.8833271861076355,
1163
+ "learning_rate": 3.438673732302223e-06,
1164
+ "loss": 1.7635,
1165
+ "step": 1650
1166
+ },
1167
+ {
1168
+ "epoch": 4.426666666666667,
1169
+ "grad_norm": 1.076093316078186,
1170
+ "learning_rate": 3.417064953471911e-06,
1171
+ "loss": 1.669,
1172
+ "step": 1660
1173
+ },
1174
+ {
1175
+ "epoch": 4.453333333333333,
1176
+ "grad_norm": 0.9731333255767822,
1177
+ "learning_rate": 3.395376714533419e-06,
1178
+ "loss": 1.6524,
1179
+ "step": 1670
1180
+ },
1181
+ {
1182
+ "epoch": 4.48,
1183
+ "grad_norm": 0.9789080619812012,
1184
+ "learning_rate": 3.3736108946882233e-06,
1185
+ "loss": 1.6656,
1186
+ "step": 1680
1187
+ },
1188
+ {
1189
+ "epoch": 4.506666666666667,
1190
+ "grad_norm": 0.8803356289863586,
1191
+ "learning_rate": 3.35176937985988e-06,
1192
+ "loss": 1.7349,
1193
+ "step": 1690
1194
+ },
1195
+ {
1196
+ "epoch": 4.533333333333333,
1197
+ "grad_norm": 0.8241089582443237,
1198
+ "learning_rate": 3.329854062530621e-06,
1199
+ "loss": 1.6017,
1200
+ "step": 1700
1201
+ },
1202
+ {
1203
+ "epoch": 4.5600000000000005,
1204
+ "grad_norm": 0.9876794815063477,
1205
+ "learning_rate": 3.307866841577381e-06,
1206
+ "loss": 1.7662,
1207
+ "step": 1710
1208
+ },
1209
+ {
1210
+ "epoch": 4.586666666666667,
1211
+ "grad_norm": 0.8717515468597412,
1212
+ "learning_rate": 3.2858096221072605e-06,
1213
+ "loss": 1.6321,
1214
+ "step": 1720
1215
+ },
1216
+ {
1217
+ "epoch": 4.613333333333333,
1218
+ "grad_norm": 0.8869647979736328,
1219
+ "learning_rate": 3.2636843152924595e-06,
1220
+ "loss": 1.6662,
1221
+ "step": 1730
1222
+ },
1223
+ {
1224
+ "epoch": 4.64,
1225
+ "grad_norm": 0.9849333763122559,
1226
+ "learning_rate": 3.241492838204684e-06,
1227
+ "loss": 1.6656,
1228
+ "step": 1740
1229
+ },
1230
+ {
1231
+ "epoch": 4.666666666666667,
1232
+ "grad_norm": 1.0160856246948242,
1233
+ "learning_rate": 3.2192371136490325e-06,
1234
+ "loss": 1.7322,
1235
+ "step": 1750
1236
+ },
1237
+ {
1238
+ "epoch": 4.693333333333333,
1239
+ "grad_norm": 1.1271207332611084,
1240
+ "learning_rate": 3.1969190699973985e-06,
1241
+ "loss": 1.635,
1242
+ "step": 1760
1243
+ },
1244
+ {
1245
+ "epoch": 4.72,
1246
+ "grad_norm": 0.8037768006324768,
1247
+ "learning_rate": 3.174540641021384e-06,
1248
+ "loss": 1.6201,
1249
+ "step": 1770
1250
+ },
1251
+ {
1252
+ "epoch": 4.746666666666667,
1253
+ "grad_norm": 0.8098615407943726,
1254
+ "learning_rate": 3.152103765724743e-06,
1255
+ "loss": 1.6724,
1256
+ "step": 1780
1257
+ },
1258
+ {
1259
+ "epoch": 4.773333333333333,
1260
+ "grad_norm": 0.9140426516532898,
1261
+ "learning_rate": 3.129610388175373e-06,
1262
+ "loss": 1.7291,
1263
+ "step": 1790
1264
+ },
1265
+ {
1266
+ "epoch": 4.8,
1267
+ "grad_norm": 0.8616933822631836,
1268
+ "learning_rate": 3.1070624573368772e-06,
1269
+ "loss": 1.7201,
1270
+ "step": 1800
1271
+ },
1272
+ {
1273
+ "epoch": 4.826666666666666,
1274
+ "grad_norm": 0.8575533032417297,
1275
+ "learning_rate": 3.0844619268996845e-06,
1276
+ "loss": 1.6765,
1277
+ "step": 1810
1278
+ },
1279
+ {
1280
+ "epoch": 4.8533333333333335,
1281
+ "grad_norm": 1.0969172716140747,
1282
+ "learning_rate": 3.061810755111776e-06,
1283
+ "loss": 1.7236,
1284
+ "step": 1820
1285
+ },
1286
+ {
1287
+ "epoch": 4.88,
1288
+ "grad_norm": 0.8472016453742981,
1289
+ "learning_rate": 3.0391109046090082e-06,
1290
+ "loss": 1.6881,
1291
+ "step": 1830
1292
+ },
1293
+ {
1294
+ "epoch": 4.906666666666666,
1295
+ "grad_norm": 0.8848344683647156,
1296
+ "learning_rate": 3.016364342245059e-06,
1297
+ "loss": 1.6624,
1298
+ "step": 1840
1299
+ },
1300
+ {
1301
+ "epoch": 4.933333333333334,
1302
+ "grad_norm": 0.8401445150375366,
1303
+ "learning_rate": 2.9935730389210076e-06,
1304
+ "loss": 1.6553,
1305
+ "step": 1850
1306
+ },
1307
+ {
1308
+ "epoch": 4.96,
1309
+ "grad_norm": 0.8503660559654236,
1310
+ "learning_rate": 2.970738969414563e-06,
1311
+ "loss": 1.6752,
1312
+ "step": 1860
1313
+ },
1314
+ {
1315
+ "epoch": 4.986666666666666,
1316
+ "grad_norm": 0.9966988563537598,
1317
+ "learning_rate": 2.9478641122089563e-06,
1318
+ "loss": 1.7338,
1319
+ "step": 1870
1320
+ },
1321
+ {
1322
+ "epoch": 5.013333333333334,
1323
+ "grad_norm": 0.602899968624115,
1324
+ "learning_rate": 2.924950449321515e-06,
1325
+ "loss": 1.5855,
1326
+ "step": 1880
1327
+ },
1328
+ {
1329
+ "epoch": 5.04,
1330
+ "grad_norm": 1.0888887643814087,
1331
+ "learning_rate": 2.9019999661319296e-06,
1332
+ "loss": 1.7572,
1333
+ "step": 1890
1334
+ },
1335
+ {
1336
+ "epoch": 5.066666666666666,
1337
+ "grad_norm": 0.95545893907547,
1338
+ "learning_rate": 2.8790146512102228e-06,
1339
+ "loss": 1.6945,
1340
+ "step": 1900
1341
+ },
1342
+ {
1343
+ "epoch": 5.093333333333334,
1344
+ "grad_norm": 0.7938442826271057,
1345
+ "learning_rate": 2.8559964961444533e-06,
1346
+ "loss": 1.6246,
1347
+ "step": 1910
1348
+ },
1349
+ {
1350
+ "epoch": 5.12,
1351
+ "grad_norm": 0.9190901517868042,
1352
+ "learning_rate": 2.8329474953681506e-06,
1353
+ "loss": 1.7174,
1354
+ "step": 1920
1355
+ },
1356
+ {
1357
+ "epoch": 5.1466666666666665,
1358
+ "grad_norm": 0.8581053614616394,
1359
+ "learning_rate": 2.8098696459875048e-06,
1360
+ "loss": 1.6249,
1361
+ "step": 1930
1362
+ },
1363
+ {
1364
+ "epoch": 5.173333333333334,
1365
+ "grad_norm": 1.1097462177276611,
1366
+ "learning_rate": 2.786764947608324e-06,
1367
+ "loss": 1.7614,
1368
+ "step": 1940
1369
+ },
1370
+ {
1371
+ "epoch": 5.2,
1372
+ "grad_norm": 0.8244250416755676,
1373
+ "learning_rate": 2.7636354021627802e-06,
1374
+ "loss": 1.6954,
1375
+ "step": 1950
1376
+ },
1377
+ {
1378
+ "epoch": 5.226666666666667,
1379
+ "grad_norm": 1.0831646919250488,
1380
+ "learning_rate": 2.7404830137359445e-06,
1381
+ "loss": 1.7215,
1382
+ "step": 1960
1383
+ },
1384
+ {
1385
+ "epoch": 5.253333333333333,
1386
+ "grad_norm": 0.8918278217315674,
1387
+ "learning_rate": 2.717309788392144e-06,
1388
+ "loss": 1.6235,
1389
+ "step": 1970
1390
+ },
1391
+ {
1392
+ "epoch": 5.28,
1393
+ "grad_norm": 0.8835996389389038,
1394
+ "learning_rate": 2.694117734001143e-06,
1395
+ "loss": 1.7047,
1396
+ "step": 1980
1397
+ },
1398
+ {
1399
+ "epoch": 5.306666666666667,
1400
+ "grad_norm": 0.8840324282646179,
1401
+ "learning_rate": 2.670908860064172e-06,
1402
+ "loss": 1.6767,
1403
+ "step": 1990
1404
+ },
1405
+ {
1406
+ "epoch": 5.333333333333333,
1407
+ "grad_norm": 1.132769227027893,
1408
+ "learning_rate": 2.6476851775398073e-06,
1409
+ "loss": 1.6917,
1410
+ "step": 2000
1411
+ },
1412
+ {
1413
+ "epoch": 5.36,
1414
+ "grad_norm": 0.9361376762390137,
1415
+ "learning_rate": 2.624448698669731e-06,
1416
+ "loss": 1.7446,
1417
+ "step": 2010
1418
+ },
1419
+ {
1420
+ "epoch": 5.386666666666667,
1421
+ "grad_norm": 0.9744315147399902,
1422
+ "learning_rate": 2.6012014368043813e-06,
1423
+ "loss": 1.7049,
1424
+ "step": 2020
1425
+ },
1426
+ {
1427
+ "epoch": 5.413333333333333,
1428
+ "grad_norm": 0.9135685563087463,
1429
+ "learning_rate": 2.5779454062285e-06,
1430
+ "loss": 1.6978,
1431
+ "step": 2030
1432
+ },
1433
+ {
1434
+ "epoch": 5.44,
1435
+ "grad_norm": 0.8381025791168213,
1436
+ "learning_rate": 2.5546826219866018e-06,
1437
+ "loss": 1.7194,
1438
+ "step": 2040
1439
+ },
1440
+ {
1441
+ "epoch": 5.466666666666667,
1442
+ "grad_norm": 1.0132782459259033,
1443
+ "learning_rate": 2.531415099708382e-06,
1444
+ "loss": 1.6255,
1445
+ "step": 2050
1446
+ },
1447
+ {
1448
+ "epoch": 5.493333333333333,
1449
+ "grad_norm": 0.836195170879364,
1450
+ "learning_rate": 2.5081448554340688e-06,
1451
+ "loss": 1.6757,
1452
+ "step": 2060
1453
+ },
1454
+ {
1455
+ "epoch": 5.52,
1456
+ "grad_norm": 1.2027889490127563,
1457
+ "learning_rate": 2.484873905439739e-06,
1458
+ "loss": 1.6886,
1459
+ "step": 2070
1460
+ },
1461
+ {
1462
+ "epoch": 5.546666666666667,
1463
+ "grad_norm": 1.023413896560669,
1464
+ "learning_rate": 2.4616042660626176e-06,
1465
+ "loss": 1.6878,
1466
+ "step": 2080
1467
+ },
1468
+ {
1469
+ "epoch": 5.573333333333333,
1470
+ "grad_norm": 0.9862648248672485,
1471
+ "learning_rate": 2.4383379535263725e-06,
1472
+ "loss": 1.6724,
1473
+ "step": 2090
1474
+ },
1475
+ {
1476
+ "epoch": 5.6,
1477
+ "grad_norm": 0.9263085126876831,
1478
+ "learning_rate": 2.4150769837664102e-06,
1479
+ "loss": 1.6894,
1480
+ "step": 2100
1481
+ },
1482
+ {
1483
+ "epoch": 5.626666666666667,
1484
+ "grad_norm": 1.2808797359466553,
1485
+ "learning_rate": 2.391823372255208e-06,
1486
+ "loss": 1.6914,
1487
+ "step": 2110
1488
+ },
1489
+ {
1490
+ "epoch": 5.653333333333333,
1491
+ "grad_norm": 1.2096583843231201,
1492
+ "learning_rate": 2.368579133827679e-06,
1493
+ "loss": 1.6269,
1494
+ "step": 2120
1495
+ },
1496
+ {
1497
+ "epoch": 5.68,
1498
+ "grad_norm": 0.9128383994102478,
1499
+ "learning_rate": 2.3453462825065966e-06,
1500
+ "loss": 1.6455,
1501
+ "step": 2130
1502
+ },
1503
+ {
1504
+ "epoch": 5.706666666666667,
1505
+ "grad_norm": 0.9094266295433044,
1506
+ "learning_rate": 2.3221268313280836e-06,
1507
+ "loss": 1.674,
1508
+ "step": 2140
1509
+ },
1510
+ {
1511
+ "epoch": 5.733333333333333,
1512
+ "grad_norm": 1.0370837450027466,
1513
+ "learning_rate": 2.2989227921671935e-06,
1514
+ "loss": 1.7358,
1515
+ "step": 2150
1516
+ },
1517
+ {
1518
+ "epoch": 5.76,
1519
+ "grad_norm": 1.0183449983596802,
1520
+ "learning_rate": 2.27573617556359e-06,
1521
+ "loss": 1.6758,
1522
+ "step": 2160
1523
+ },
1524
+ {
1525
+ "epoch": 5.786666666666667,
1526
+ "grad_norm": 0.7834766507148743,
1527
+ "learning_rate": 2.2525689905473377e-06,
1528
+ "loss": 1.64,
1529
+ "step": 2170
1530
+ },
1531
+ {
1532
+ "epoch": 5.8133333333333335,
1533
+ "grad_norm": 0.9842936992645264,
1534
+ "learning_rate": 2.2294232444648316e-06,
1535
+ "loss": 1.5864,
1536
+ "step": 2180
1537
+ },
1538
+ {
1539
+ "epoch": 5.84,
1540
+ "grad_norm": 0.9197008609771729,
1541
+ "learning_rate": 2.206300942804865e-06,
1542
+ "loss": 1.6242,
1543
+ "step": 2190
1544
+ },
1545
+ {
1546
+ "epoch": 5.866666666666667,
1547
+ "grad_norm": 0.9002187252044678,
1548
+ "learning_rate": 2.183204089024864e-06,
1549
+ "loss": 1.7396,
1550
+ "step": 2200
1551
+ },
1552
+ {
1553
+ "epoch": 5.8933333333333335,
1554
+ "grad_norm": 0.894535481929779,
1555
+ "learning_rate": 2.160134684377295e-06,
1556
+ "loss": 1.6573,
1557
+ "step": 2210
1558
+ },
1559
+ {
1560
+ "epoch": 5.92,
1561
+ "grad_norm": 0.7890879511833191,
1562
+ "learning_rate": 2.1370947277362646e-06,
1563
+ "loss": 1.6712,
1564
+ "step": 2220
1565
+ },
1566
+ {
1567
+ "epoch": 5.946666666666666,
1568
+ "grad_norm": 0.7837865352630615,
1569
+ "learning_rate": 2.1140862154243223e-06,
1570
+ "loss": 1.6761,
1571
+ "step": 2230
1572
+ },
1573
+ {
1574
+ "epoch": 5.973333333333334,
1575
+ "grad_norm": 0.9894525408744812,
1576
+ "learning_rate": 2.0911111410394915e-06,
1577
+ "loss": 1.5695,
1578
+ "step": 2240
1579
+ },
1580
+ {
1581
+ "epoch": 6.0,
1582
+ "grad_norm": 0.9099172353744507,
1583
+ "learning_rate": 2.0681714952825274e-06,
1584
+ "loss": 1.6609,
1585
+ "step": 2250
1586
+ },
1587
+ {
1588
+ "epoch": 6.026666666666666,
1589
+ "grad_norm": 0.8880329728126526,
1590
+ "learning_rate": 2.0452692657844333e-06,
1591
+ "loss": 1.6532,
1592
+ "step": 2260
1593
+ },
1594
+ {
1595
+ "epoch": 6.053333333333334,
1596
+ "grad_norm": 1.021958351135254,
1597
+ "learning_rate": 2.0224064369342388e-06,
1598
+ "loss": 1.7392,
1599
+ "step": 2270
1600
+ },
1601
+ {
1602
+ "epoch": 6.08,
1603
+ "grad_norm": 1.2252111434936523,
1604
+ "learning_rate": 1.9995849897070616e-06,
1605
+ "loss": 1.6888,
1606
+ "step": 2280
1607
+ },
1608
+ {
1609
+ "epoch": 6.1066666666666665,
1610
+ "grad_norm": 1.0892808437347412,
1611
+ "learning_rate": 1.9768069014924622e-06,
1612
+ "loss": 1.569,
1613
+ "step": 2290
1614
+ },
1615
+ {
1616
+ "epoch": 6.133333333333334,
1617
+ "grad_norm": 1.123616099357605,
1618
+ "learning_rate": 1.9540741459231124e-06,
1619
+ "loss": 1.6742,
1620
+ "step": 2300
1621
+ },
1622
+ {
1623
+ "epoch": 6.16,
1624
+ "grad_norm": 1.00949227809906,
1625
+ "learning_rate": 1.9313886927037843e-06,
1626
+ "loss": 1.6555,
1627
+ "step": 2310
1628
+ },
1629
+ {
1630
+ "epoch": 6.1866666666666665,
1631
+ "grad_norm": 0.8746801018714905,
1632
+ "learning_rate": 1.908752507440689e-06,
1633
+ "loss": 1.7283,
1634
+ "step": 2320
1635
+ },
1636
+ {
1637
+ "epoch": 6.213333333333333,
1638
+ "grad_norm": 0.9742733836174011,
1639
+ "learning_rate": 1.8861675514711572e-06,
1640
+ "loss": 1.6918,
1641
+ "step": 2330
1642
+ },
1643
+ {
1644
+ "epoch": 6.24,
1645
+ "grad_norm": 1.311090111732483,
1646
+ "learning_rate": 1.863635781693705e-06,
1647
+ "loss": 1.6135,
1648
+ "step": 2340
1649
+ },
1650
+ {
1651
+ "epoch": 6.266666666666667,
1652
+ "grad_norm": 1.0751314163208008,
1653
+ "learning_rate": 1.8411591503984687e-06,
1654
+ "loss": 1.6877,
1655
+ "step": 2350
1656
+ },
1657
+ {
1658
+ "epoch": 6.293333333333333,
1659
+ "grad_norm": 0.9745664000511169,
1660
+ "learning_rate": 1.818739605098051e-06,
1661
+ "loss": 1.7167,
1662
+ "step": 2360
1663
+ },
1664
+ {
1665
+ "epoch": 6.32,
1666
+ "grad_norm": 1.391249656677246,
1667
+ "learning_rate": 1.796379088358775e-06,
1668
+ "loss": 1.6697,
1669
+ "step": 2370
1670
+ },
1671
+ {
1672
+ "epoch": 6.346666666666667,
1673
+ "grad_norm": 1.0126644372940063,
1674
+ "learning_rate": 1.774079537632369e-06,
1675
+ "loss": 1.6313,
1676
+ "step": 2380
1677
+ },
1678
+ {
1679
+ "epoch": 6.373333333333333,
1680
+ "grad_norm": 0.9063668847084045,
1681
+ "learning_rate": 1.7518428850880928e-06,
1682
+ "loss": 1.6423,
1683
+ "step": 2390
1684
+ },
1685
+ {
1686
+ "epoch": 6.4,
1687
+ "grad_norm": 0.9129550457000732,
1688
+ "learning_rate": 1.7296710574453262e-06,
1689
+ "loss": 1.6806,
1690
+ "step": 2400
1691
+ },
1692
+ {
1693
+ "epoch": 6.426666666666667,
1694
+ "grad_norm": 1.0306205749511719,
1695
+ "learning_rate": 1.7075659758066207e-06,
1696
+ "loss": 1.8324,
1697
+ "step": 2410
1698
+ },
1699
+ {
1700
+ "epoch": 6.453333333333333,
1701
+ "grad_norm": 0.9289770126342773,
1702
+ "learning_rate": 1.6855295554912477e-06,
1703
+ "loss": 1.7036,
1704
+ "step": 2420
1705
+ },
1706
+ {
1707
+ "epoch": 6.48,
1708
+ "grad_norm": 1.1734378337860107,
1709
+ "learning_rate": 1.6635637058692417e-06,
1710
+ "loss": 1.7271,
1711
+ "step": 2430
1712
+ },
1713
+ {
1714
+ "epoch": 6.506666666666667,
1715
+ "grad_norm": 1.1899135112762451,
1716
+ "learning_rate": 1.6416703301959622e-06,
1717
+ "loss": 1.6116,
1718
+ "step": 2440
1719
+ },
1720
+ {
1721
+ "epoch": 6.533333333333333,
1722
+ "grad_norm": 0.9925697445869446,
1723
+ "learning_rate": 1.619851325447182e-06,
1724
+ "loss": 1.65,
1725
+ "step": 2450
1726
+ },
1727
+ {
1728
+ "epoch": 6.5600000000000005,
1729
+ "grad_norm": 1.0551037788391113,
1730
+ "learning_rate": 1.5981085821547237e-06,
1731
+ "loss": 1.6553,
1732
+ "step": 2460
1733
+ },
1734
+ {
1735
+ "epoch": 6.586666666666667,
1736
+ "grad_norm": 0.9644522666931152,
1737
+ "learning_rate": 1.5764439842426516e-06,
1738
+ "loss": 1.6487,
1739
+ "step": 2470
1740
+ },
1741
+ {
1742
+ "epoch": 6.613333333333333,
1743
+ "grad_norm": 1.1285290718078613,
1744
+ "learning_rate": 1.5548594088640368e-06,
1745
+ "loss": 1.692,
1746
+ "step": 2480
1747
+ },
1748
+ {
1749
+ "epoch": 6.64,
1750
+ "grad_norm": 1.2168961763381958,
1751
+ "learning_rate": 1.5333567262383086e-06,
1752
+ "loss": 1.6596,
1753
+ "step": 2490
1754
+ },
1755
+ {
1756
+ "epoch": 6.666666666666667,
1757
+ "grad_norm": 1.0515251159667969,
1758
+ "learning_rate": 1.5119377994892095e-06,
1759
+ "loss": 1.603,
1760
+ "step": 2500
1761
+ },
1762
+ {
1763
+ "epoch": 6.693333333333333,
1764
+ "grad_norm": 1.0192151069641113,
1765
+ "learning_rate": 1.4906044844833605e-06,
1766
+ "loss": 1.6846,
1767
+ "step": 2510
1768
+ },
1769
+ {
1770
+ "epoch": 6.72,
1771
+ "grad_norm": 1.1747512817382812,
1772
+ "learning_rate": 1.4693586296694574e-06,
1773
+ "loss": 1.6895,
1774
+ "step": 2520
1775
+ },
1776
+ {
1777
+ "epoch": 6.746666666666667,
1778
+ "grad_norm": 1.0625276565551758,
1779
+ "learning_rate": 1.4482020759181136e-06,
1780
+ "loss": 1.6625,
1781
+ "step": 2530
1782
+ },
1783
+ {
1784
+ "epoch": 6.773333333333333,
1785
+ "grad_norm": 1.2509487867355347,
1786
+ "learning_rate": 1.4271366563623512e-06,
1787
+ "loss": 1.6851,
1788
+ "step": 2540
1789
+ },
1790
+ {
1791
+ "epoch": 6.8,
1792
+ "grad_norm": 1.12450110912323,
1793
+ "learning_rate": 1.406164196238768e-06,
1794
+ "loss": 1.6029,
1795
+ "step": 2550
1796
+ },
1797
+ {
1798
+ "epoch": 6.826666666666666,
1799
+ "grad_norm": 1.1328859329223633,
1800
+ "learning_rate": 1.3852865127293901e-06,
1801
+ "loss": 1.5987,
1802
+ "step": 2560
1803
+ },
1804
+ {
1805
+ "epoch": 6.8533333333333335,
1806
+ "grad_norm": 1.0585845708847046,
1807
+ "learning_rate": 1.364505414804221e-06,
1808
+ "loss": 1.6181,
1809
+ "step": 2570
1810
+ },
1811
+ {
1812
+ "epoch": 6.88,
1813
+ "grad_norm": 1.2313337326049805,
1814
+ "learning_rate": 1.3438227030644946e-06,
1815
+ "loss": 1.7003,
1816
+ "step": 2580
1817
+ },
1818
+ {
1819
+ "epoch": 6.906666666666666,
1820
+ "grad_norm": 1.1627655029296875,
1821
+ "learning_rate": 1.3232401695866686e-06,
1822
+ "loss": 1.6519,
1823
+ "step": 2590
1824
+ },
1825
+ {
1826
+ "epoch": 6.933333333333334,
1827
+ "grad_norm": 1.4945528507232666,
1828
+ "learning_rate": 1.3027595977671443e-06,
1829
+ "loss": 1.6431,
1830
+ "step": 2600
1831
+ },
1832
+ {
1833
+ "epoch": 6.96,
1834
+ "grad_norm": 1.0905581712722778,
1835
+ "learning_rate": 1.282382762167739e-06,
1836
+ "loss": 1.6311,
1837
+ "step": 2610
1838
+ },
1839
+ {
1840
+ "epoch": 6.986666666666666,
1841
+ "grad_norm": 1.1594579219818115,
1842
+ "learning_rate": 1.2621114283619345e-06,
1843
+ "loss": 1.7169,
1844
+ "step": 2620
1845
+ },
1846
+ {
1847
+ "epoch": 7.013333333333334,
1848
+ "grad_norm": 1.0197468996047974,
1849
+ "learning_rate": 1.241947352781889e-06,
1850
+ "loss": 1.6843,
1851
+ "step": 2630
1852
+ },
1853
+ {
1854
+ "epoch": 7.04,
1855
+ "grad_norm": 0.9002560973167419,
1856
+ "learning_rate": 1.2218922825662558e-06,
1857
+ "loss": 1.6436,
1858
+ "step": 2640
1859
+ },
1860
+ {
1861
+ "epoch": 7.066666666666666,
1862
+ "grad_norm": 1.0222526788711548,
1863
+ "learning_rate": 1.2019479554087964e-06,
1864
+ "loss": 1.6276,
1865
+ "step": 2650
1866
+ },
1867
+ {
1868
+ "epoch": 7.093333333333334,
1869
+ "grad_norm": 1.2399083375930786,
1870
+ "learning_rate": 1.182116099407819e-06,
1871
+ "loss": 1.6515,
1872
+ "step": 2660
1873
+ },
1874
+ {
1875
+ "epoch": 7.12,
1876
+ "grad_norm": 1.0906753540039062,
1877
+ "learning_rate": 1.1623984329164413e-06,
1878
+ "loss": 1.6438,
1879
+ "step": 2670
1880
+ },
1881
+ {
1882
+ "epoch": 7.1466666666666665,
1883
+ "grad_norm": 1.0210061073303223,
1884
+ "learning_rate": 1.142796664393707e-06,
1885
+ "loss": 1.705,
1886
+ "step": 2680
1887
+ },
1888
+ {
1889
+ "epoch": 7.173333333333334,
1890
+ "grad_norm": 0.9715026617050171,
1891
+ "learning_rate": 1.1233124922565494e-06,
1892
+ "loss": 1.7126,
1893
+ "step": 2690
1894
+ },
1895
+ {
1896
+ "epoch": 7.2,
1897
+ "grad_norm": 0.8580982685089111,
1898
+ "learning_rate": 1.1039476047326352e-06,
1899
+ "loss": 1.6729,
1900
+ "step": 2700
1901
+ },
1902
+ {
1903
+ "epoch": 7.226666666666667,
1904
+ "grad_norm": 1.1537833213806152,
1905
+ "learning_rate": 1.0847036797140832e-06,
1906
+ "loss": 1.7293,
1907
+ "step": 2710
1908
+ },
1909
+ {
1910
+ "epoch": 7.253333333333333,
1911
+ "grad_norm": 0.998429536819458,
1912
+ "learning_rate": 1.065582384612082e-06,
1913
+ "loss": 1.7036,
1914
+ "step": 2720
1915
+ },
1916
+ {
1917
+ "epoch": 7.28,
1918
+ "grad_norm": 1.0259299278259277,
1919
+ "learning_rate": 1.0465853762124134e-06,
1920
+ "loss": 1.6303,
1921
+ "step": 2730
1922
+ },
1923
+ {
1924
+ "epoch": 7.306666666666667,
1925
+ "grad_norm": 1.121588110923767,
1926
+ "learning_rate": 1.0277143005319038e-06,
1927
+ "loss": 1.6615,
1928
+ "step": 2740
1929
+ },
1930
+ {
1931
+ "epoch": 7.333333333333333,
1932
+ "grad_norm": 0.9042307138442993,
1933
+ "learning_rate": 1.0089707926757954e-06,
1934
+ "loss": 1.6152,
1935
+ "step": 2750
1936
+ },
1937
+ {
1938
+ "epoch": 7.36,
1939
+ "grad_norm": 0.9918031692504883,
1940
+ "learning_rate": 9.9035647669608e-07,
1941
+ "loss": 1.5828,
1942
+ "step": 2760
1943
+ },
1944
+ {
1945
+ "epoch": 7.386666666666667,
1946
+ "grad_norm": 1.0638200044631958,
1947
+ "learning_rate": 9.718729654507713e-07,
1948
+ "loss": 1.6624,
1949
+ "step": 2770
1950
+ },
1951
+ {
1952
+ "epoch": 7.413333333333333,
1953
+ "grad_norm": 1.013146996498108,
1954
+ "learning_rate": 9.535218604641652e-07,
1955
+ "loss": 1.7115,
1956
+ "step": 2780
1957
+ },
1958
+ {
1959
+ "epoch": 7.44,
1960
+ "grad_norm": 1.302118182182312,
1961
+ "learning_rate": 9.353047517880709e-07,
1962
+ "loss": 1.638,
1963
+ "step": 2790
1964
+ },
1965
+ {
1966
+ "epoch": 7.466666666666667,
1967
+ "grad_norm": 0.7931357622146606,
1968
+ "learning_rate": 9.172232178640361e-07,
1969
+ "loss": 1.7482,
1970
+ "step": 2800
1971
+ },
1972
+ {
1973
+ "epoch": 7.493333333333333,
1974
+ "grad_norm": 0.9321092367172241,
1975
+ "learning_rate": 8.992788253865872e-07,
1976
+ "loss": 1.6079,
1977
+ "step": 2810
1978
+ },
1979
+ {
1980
+ "epoch": 7.52,
1981
+ "grad_norm": 1.0876185894012451,
1982
+ "learning_rate": 8.814731291674756e-07,
1983
+ "loss": 1.6749,
1984
+ "step": 2820
1985
+ },
1986
+ {
1987
+ "epoch": 7.546666666666667,
1988
+ "grad_norm": 1.0826046466827393,
1989
+ "learning_rate": 8.63807672000963e-07,
1990
+ "loss": 1.6491,
1991
+ "step": 2830
1992
+ },
1993
+ {
1994
+ "epoch": 7.573333333333333,
1995
+ "grad_norm": 1.0835968255996704,
1996
+ "learning_rate": 8.462839845301438e-07,
1997
+ "loss": 1.6671,
1998
+ "step": 2840
1999
+ },
2000
+ {
2001
+ "epoch": 7.6,
2002
+ "grad_norm": 1.2509957551956177,
2003
+ "learning_rate": 8.289035851143198e-07,
2004
+ "loss": 1.67,
2005
+ "step": 2850
2006
+ },
2007
+ {
2008
+ "epoch": 7.626666666666667,
2009
+ "grad_norm": 1.1528269052505493,
2010
+ "learning_rate": 8.116679796974389e-07,
2011
+ "loss": 1.6247,
2012
+ "step": 2860
2013
+ },
2014
+ {
2015
+ "epoch": 7.653333333333333,
2016
+ "grad_norm": 0.9256828427314758,
2017
+ "learning_rate": 7.945786616776157e-07,
2018
+ "loss": 1.6268,
2019
+ "step": 2870
2020
+ },
2021
+ {
2022
+ "epoch": 7.68,
2023
+ "grad_norm": 1.0600520372390747,
2024
+ "learning_rate": 7.776371117777276e-07,
2025
+ "loss": 1.6902,
2026
+ "step": 2880
2027
+ },
2028
+ {
2029
+ "epoch": 7.706666666666667,
2030
+ "grad_norm": 0.9527045488357544,
2031
+ "learning_rate": 7.60844797917123e-07,
2032
+ "loss": 1.5988,
2033
+ "step": 2890
2034
+ },
2035
+ {
2036
+ "epoch": 7.733333333333333,
2037
+ "grad_norm": 1.0828256607055664,
2038
+ "learning_rate": 7.442031750844269e-07,
2039
+ "loss": 1.6704,
2040
+ "step": 2900
2041
+ },
2042
+ {
2043
+ "epoch": 7.76,
2044
+ "grad_norm": 1.1773947477340698,
2045
+ "learning_rate": 7.277136852114747e-07,
2046
+ "loss": 1.6827,
2047
+ "step": 2910
2048
+ },
2049
+ {
2050
+ "epoch": 7.786666666666667,
2051
+ "grad_norm": 1.3546745777130127,
2052
+ "learning_rate": 7.113777570483701e-07,
2053
+ "loss": 1.6406,
2054
+ "step": 2920
2055
+ },
2056
+ {
2057
+ "epoch": 7.8133333333333335,
2058
+ "grad_norm": 1.0221235752105713,
2059
+ "learning_rate": 6.951968060396963e-07,
2060
+ "loss": 1.6239,
2061
+ "step": 2930
2062
+ },
2063
+ {
2064
+ "epoch": 7.84,
2065
+ "grad_norm": 0.8836374282836914,
2066
+ "learning_rate": 6.791722342018656e-07,
2067
+ "loss": 1.6505,
2068
+ "step": 2940
2069
+ },
2070
+ {
2071
+ "epoch": 7.866666666666667,
2072
+ "grad_norm": 1.4861336946487427,
2073
+ "learning_rate": 6.633054300016464e-07,
2074
+ "loss": 1.6439,
2075
+ "step": 2950
2076
+ },
2077
+ {
2078
+ "epoch": 7.8933333333333335,
2079
+ "grad_norm": 1.0975189208984375,
2080
+ "learning_rate": 6.475977682358558e-07,
2081
+ "loss": 1.6943,
2082
+ "step": 2960
2083
+ },
2084
+ {
2085
+ "epoch": 7.92,
2086
+ "grad_norm": 0.9906185269355774,
2087
+ "learning_rate": 6.320506099122359e-07,
2088
+ "loss": 1.6972,
2089
+ "step": 2970
2090
+ },
2091
+ {
2092
+ "epoch": 7.946666666666666,
2093
+ "grad_norm": 0.9991128444671631,
2094
+ "learning_rate": 6.166653021315336e-07,
2095
+ "loss": 1.7144,
2096
+ "step": 2980
2097
+ },
2098
+ {
2099
+ "epoch": 7.973333333333334,
2100
+ "grad_norm": 0.7832310795783997,
2101
+ "learning_rate": 6.01443177970773e-07,
2102
+ "loss": 1.64,
2103
+ "step": 2990
2104
+ },
2105
+ {
2106
+ "epoch": 8.0,
2107
+ "grad_norm": 1.045725703239441,
2108
+ "learning_rate": 5.863855563677559e-07,
2109
+ "loss": 1.6638,
2110
+ "step": 3000
2111
+ },
2112
+ {
2113
+ "epoch": 8.026666666666667,
2114
+ "grad_norm": 0.9321222901344299,
2115
+ "learning_rate": 5.714937420067746e-07,
2116
+ "loss": 1.6576,
2117
+ "step": 3010
2118
+ },
2119
+ {
2120
+ "epoch": 8.053333333333333,
2121
+ "grad_norm": 1.1314470767974854,
2122
+ "learning_rate": 5.567690252055738e-07,
2123
+ "loss": 1.634,
2124
+ "step": 3020
2125
+ },
2126
+ {
2127
+ "epoch": 8.08,
2128
+ "grad_norm": 1.1661452054977417,
2129
+ "learning_rate": 5.422126818035403e-07,
2130
+ "loss": 1.6576,
2131
+ "step": 3030
2132
+ },
2133
+ {
2134
+ "epoch": 8.106666666666667,
2135
+ "grad_norm": 1.023749589920044,
2136
+ "learning_rate": 5.278259730511651e-07,
2137
+ "loss": 1.6985,
2138
+ "step": 3040
2139
+ },
2140
+ {
2141
+ "epoch": 8.133333333333333,
2142
+ "grad_norm": 0.8616606593132019,
2143
+ "learning_rate": 5.136101455007541e-07,
2144
+ "loss": 1.7006,
2145
+ "step": 3050
2146
+ },
2147
+ {
2148
+ "epoch": 8.16,
2149
+ "grad_norm": 1.0434175729751587,
2150
+ "learning_rate": 4.995664308984254e-07,
2151
+ "loss": 1.6621,
2152
+ "step": 3060
2153
+ },
2154
+ {
2155
+ "epoch": 8.186666666666667,
2156
+ "grad_norm": 1.206966519355774,
2157
+ "learning_rate": 4.856960460773766e-07,
2158
+ "loss": 1.6407,
2159
+ "step": 3070
2160
+ },
2161
+ {
2162
+ "epoch": 8.213333333333333,
2163
+ "grad_norm": 0.9314172863960266,
2164
+ "learning_rate": 4.7200019285245867e-07,
2165
+ "loss": 1.7501,
2166
+ "step": 3080
2167
+ },
2168
+ {
2169
+ "epoch": 8.24,
2170
+ "grad_norm": 1.2337085008621216,
2171
+ "learning_rate": 4.5848005791603533e-07,
2172
+ "loss": 1.6169,
2173
+ "step": 3090
2174
+ },
2175
+ {
2176
+ "epoch": 8.266666666666667,
2177
+ "grad_norm": 0.9701104164123535,
2178
+ "learning_rate": 4.451368127351674e-07,
2179
+ "loss": 1.6666,
2180
+ "step": 3100
2181
+ },
2182
+ {
2183
+ "epoch": 8.293333333333333,
2184
+ "grad_norm": 1.1220892667770386,
2185
+ "learning_rate": 4.319716134501051e-07,
2186
+ "loss": 1.5962,
2187
+ "step": 3110
2188
+ },
2189
+ {
2190
+ "epoch": 8.32,
2191
+ "grad_norm": 1.0029473304748535,
2192
+ "learning_rate": 4.1898560077411664e-07,
2193
+ "loss": 1.6603,
2194
+ "step": 3120
2195
+ },
2196
+ {
2197
+ "epoch": 8.346666666666668,
2198
+ "grad_norm": 1.011228084564209,
2199
+ "learning_rate": 4.061798998946459e-07,
2200
+ "loss": 1.6106,
2201
+ "step": 3130
2202
+ },
2203
+ {
2204
+ "epoch": 8.373333333333333,
2205
+ "grad_norm": 1.3020498752593994,
2206
+ "learning_rate": 3.935556203758237e-07,
2207
+ "loss": 1.669,
2208
+ "step": 3140
2209
+ },
2210
+ {
2211
+ "epoch": 8.4,
2212
+ "grad_norm": 1.105768084526062,
2213
+ "learning_rate": 3.8111385606232565e-07,
2214
+ "loss": 1.672,
2215
+ "step": 3150
2216
+ },
2217
+ {
2218
+ "epoch": 8.426666666666666,
2219
+ "grad_norm": 1.1611669063568115,
2220
+ "learning_rate": 3.6885568498459395e-07,
2221
+ "loss": 1.6565,
2222
+ "step": 3160
2223
+ },
2224
+ {
2225
+ "epoch": 8.453333333333333,
2226
+ "grad_norm": 0.9635624289512634,
2227
+ "learning_rate": 3.5678216926543384e-07,
2228
+ "loss": 1.6181,
2229
+ "step": 3170
2230
+ },
2231
+ {
2232
+ "epoch": 8.48,
2233
+ "grad_norm": 1.1056032180786133,
2234
+ "learning_rate": 3.448943550279804e-07,
2235
+ "loss": 1.6407,
2236
+ "step": 3180
2237
+ },
2238
+ {
2239
+ "epoch": 8.506666666666666,
2240
+ "grad_norm": 1.136650800704956,
2241
+ "learning_rate": 3.331932723050596e-07,
2242
+ "loss": 1.6685,
2243
+ "step": 3190
2244
+ },
2245
+ {
2246
+ "epoch": 8.533333333333333,
2247
+ "grad_norm": 0.9246675968170166,
2248
+ "learning_rate": 3.216799349499383e-07,
2249
+ "loss": 1.6401,
2250
+ "step": 3200
2251
+ },
2252
+ {
2253
+ "epoch": 8.56,
2254
+ "grad_norm": 1.0271546840667725,
2255
+ "learning_rate": 3.1035534054847884e-07,
2256
+ "loss": 1.6806,
2257
+ "step": 3210
2258
+ },
2259
+ {
2260
+ "epoch": 8.586666666666666,
2261
+ "grad_norm": 1.0452704429626465,
2262
+ "learning_rate": 2.992204703326995e-07,
2263
+ "loss": 1.6791,
2264
+ "step": 3220
2265
+ },
2266
+ {
2267
+ "epoch": 8.613333333333333,
2268
+ "grad_norm": 1.186958909034729,
2269
+ "learning_rate": 2.882762890957586e-07,
2270
+ "loss": 1.7309,
2271
+ "step": 3230
2272
+ },
2273
+ {
2274
+ "epoch": 8.64,
2275
+ "grad_norm": 1.1407443284988403,
2276
+ "learning_rate": 2.7752374510835456e-07,
2277
+ "loss": 1.6452,
2278
+ "step": 3240
2279
+ },
2280
+ {
2281
+ "epoch": 8.666666666666666,
2282
+ "grad_norm": 1.0465816259384155,
2283
+ "learning_rate": 2.6696377003656654e-07,
2284
+ "loss": 1.6748,
2285
+ "step": 3250
2286
+ },
2287
+ {
2288
+ "epoch": 8.693333333333333,
2289
+ "grad_norm": 1.1659401655197144,
2290
+ "learning_rate": 2.565972788611243e-07,
2291
+ "loss": 1.6536,
2292
+ "step": 3260
2293
+ },
2294
+ {
2295
+ "epoch": 8.72,
2296
+ "grad_norm": 1.190261960029602,
2297
+ "learning_rate": 2.46425169798134e-07,
2298
+ "loss": 1.7099,
2299
+ "step": 3270
2300
+ },
2301
+ {
2302
+ "epoch": 8.746666666666666,
2303
+ "grad_norm": 1.4275482892990112,
2304
+ "learning_rate": 2.3644832422124565e-07,
2305
+ "loss": 1.6508,
2306
+ "step": 3280
2307
+ },
2308
+ {
2309
+ "epoch": 8.773333333333333,
2310
+ "grad_norm": 0.7873063087463379,
2311
+ "learning_rate": 2.2666760658529103e-07,
2312
+ "loss": 1.5954,
2313
+ "step": 3290
2314
+ },
2315
+ {
2316
+ "epoch": 8.8,
2317
+ "grad_norm": 1.0107383728027344,
2318
+ "learning_rate": 2.1708386435137647e-07,
2319
+ "loss": 1.6384,
2320
+ "step": 3300
2321
+ },
2322
+ {
2323
+ "epoch": 8.826666666666666,
2324
+ "grad_norm": 1.151199221611023,
2325
+ "learning_rate": 2.0769792791345945e-07,
2326
+ "loss": 1.5958,
2327
+ "step": 3310
2328
+ },
2329
+ {
2330
+ "epoch": 8.853333333333333,
2331
+ "grad_norm": 0.9328808188438416,
2332
+ "learning_rate": 1.9851061052639202e-07,
2333
+ "loss": 1.7356,
2334
+ "step": 3320
2335
+ },
2336
+ {
2337
+ "epoch": 8.88,
2338
+ "grad_norm": 1.2401057481765747,
2339
+ "learning_rate": 1.8952270823546253e-07,
2340
+ "loss": 1.6644,
2341
+ "step": 3330
2342
+ },
2343
+ {
2344
+ "epoch": 8.906666666666666,
2345
+ "grad_norm": 1.0410566329956055,
2346
+ "learning_rate": 1.8073499980741426e-07,
2347
+ "loss": 1.6447,
2348
+ "step": 3340
2349
+ },
2350
+ {
2351
+ "epoch": 8.933333333333334,
2352
+ "grad_norm": 0.9945191144943237,
2353
+ "learning_rate": 1.721482466629737e-07,
2354
+ "loss": 1.63,
2355
+ "step": 3350
2356
+ },
2357
+ {
2358
+ "epoch": 8.96,
2359
+ "grad_norm": 1.384772539138794,
2360
+ "learning_rate": 1.637631928108721e-07,
2361
+ "loss": 1.5961,
2362
+ "step": 3360
2363
+ },
2364
+ {
2365
+ "epoch": 8.986666666666666,
2366
+ "grad_norm": 1.1313170194625854,
2367
+ "learning_rate": 1.5558056478338523e-07,
2368
+ "loss": 1.6825,
2369
+ "step": 3370
2370
+ },
2371
+ {
2372
+ "epoch": 9.013333333333334,
2373
+ "grad_norm": 1.0066853761672974,
2374
+ "learning_rate": 1.476010715733761e-07,
2375
+ "loss": 1.6951,
2376
+ "step": 3380
2377
+ },
2378
+ {
2379
+ "epoch": 9.04,
2380
+ "grad_norm": 1.199820637702942,
2381
+ "learning_rate": 1.3982540457286893e-07,
2382
+ "loss": 1.6796,
2383
+ "step": 3390
2384
+ },
2385
+ {
2386
+ "epoch": 9.066666666666666,
2387
+ "grad_norm": 1.135715126991272,
2388
+ "learning_rate": 1.3225423751313942e-07,
2389
+ "loss": 1.6329,
2390
+ "step": 3400
2391
+ },
2392
+ {
2393
+ "epoch": 9.093333333333334,
2394
+ "grad_norm": 1.0266982316970825,
2395
+ "learning_rate": 1.248882264063389e-07,
2396
+ "loss": 1.6754,
2397
+ "step": 3410
2398
+ },
2399
+ {
2400
+ "epoch": 9.12,
2401
+ "grad_norm": 1.192221999168396,
2402
+ "learning_rate": 1.1772800948865542e-07,
2403
+ "loss": 1.7027,
2404
+ "step": 3420
2405
+ },
2406
+ {
2407
+ "epoch": 9.146666666666667,
2408
+ "grad_norm": 1.3425045013427734,
2409
+ "learning_rate": 1.1077420716501031e-07,
2410
+ "loss": 1.6439,
2411
+ "step": 3430
2412
+ },
2413
+ {
2414
+ "epoch": 9.173333333333334,
2415
+ "grad_norm": 1.2292110919952393,
2416
+ "learning_rate": 1.0402742195530501e-07,
2417
+ "loss": 1.6746,
2418
+ "step": 3440
2419
+ },
2420
+ {
2421
+ "epoch": 9.2,
2422
+ "grad_norm": 0.9197198152542114,
2423
+ "learning_rate": 9.748823844221239e-08,
2424
+ "loss": 1.6584,
2425
+ "step": 3450
2426
+ },
2427
+ {
2428
+ "epoch": 9.226666666666667,
2429
+ "grad_norm": 0.9650914669036865,
2430
+ "learning_rate": 9.115722322052878e-08,
2431
+ "loss": 1.6752,
2432
+ "step": 3460
2433
+ },
2434
+ {
2435
+ "epoch": 9.253333333333334,
2436
+ "grad_norm": 1.2544925212860107,
2437
+ "learning_rate": 8.503492484807613e-08,
2438
+ "loss": 1.6303,
2439
+ "step": 3470
2440
+ },
2441
+ {
2442
+ "epoch": 9.28,
2443
+ "grad_norm": 1.1284185647964478,
2444
+ "learning_rate": 7.912187379817582e-08,
2445
+ "loss": 1.6722,
2446
+ "step": 3480
2447
+ },
2448
+ {
2449
+ "epoch": 9.306666666666667,
2450
+ "grad_norm": 1.0232893228530884,
2451
+ "learning_rate": 7.341858241368182e-08,
2452
+ "loss": 1.7343,
2453
+ "step": 3490
2454
+ },
2455
+ {
2456
+ "epoch": 9.333333333333334,
2457
+ "grad_norm": 1.286456823348999,
2458
+ "learning_rate": 6.79255448625904e-08,
2459
+ "loss": 1.6559,
2460
+ "step": 3500
2461
+ },
2462
+ {
2463
+ "epoch": 9.36,
2464
+ "grad_norm": 0.9723238348960876,
2465
+ "learning_rate": 6.264323709522125e-08,
2466
+ "loss": 1.7105,
2467
+ "step": 3510
2468
+ },
2469
+ {
2470
+ "epoch": 9.386666666666667,
2471
+ "grad_norm": 0.915547251701355,
2472
+ "learning_rate": 5.7572116802979695e-08,
2473
+ "loss": 1.6813,
2474
+ "step": 3520
2475
+ },
2476
+ {
2477
+ "epoch": 9.413333333333334,
2478
+ "grad_norm": 1.073350191116333,
2479
+ "learning_rate": 5.2712623378697035e-08,
2480
+ "loss": 1.662,
2481
+ "step": 3530
2482
+ },
2483
+ {
2484
+ "epoch": 9.44,
2485
+ "grad_norm": 1.4046480655670166,
2486
+ "learning_rate": 4.806517787856152e-08,
2487
+ "loss": 1.6464,
2488
+ "step": 3540
2489
+ },
2490
+ {
2491
+ "epoch": 9.466666666666667,
2492
+ "grad_norm": 0.9930236339569092,
2493
+ "learning_rate": 4.3630182985633093e-08,
2494
+ "loss": 1.5746,
2495
+ "step": 3550
2496
+ },
2497
+ {
2498
+ "epoch": 9.493333333333334,
2499
+ "grad_norm": 0.9176751375198364,
2500
+ "learning_rate": 3.940802297495466e-08,
2501
+ "loss": 1.6134,
2502
+ "step": 3560
2503
+ },
2504
+ {
2505
+ "epoch": 9.52,
2506
+ "grad_norm": 1.1889771223068237,
2507
+ "learning_rate": 3.539906368025453e-08,
2508
+ "loss": 1.6769,
2509
+ "step": 3570
2510
+ },
2511
+ {
2512
+ "epoch": 9.546666666666667,
2513
+ "grad_norm": 1.149104118347168,
2514
+ "learning_rate": 3.1603652462249e-08,
2515
+ "loss": 1.6366,
2516
+ "step": 3580
2517
+ },
2518
+ {
2519
+ "epoch": 9.573333333333334,
2520
+ "grad_norm": 0.9914628863334656,
2521
+ "learning_rate": 2.802211817854561e-08,
2522
+ "loss": 1.6296,
2523
+ "step": 3590
2524
+ },
2525
+ {
2526
+ "epoch": 9.6,
2527
+ "grad_norm": 0.9465372562408447,
2528
+ "learning_rate": 2.465477115514675e-08,
2529
+ "loss": 1.6666,
2530
+ "step": 3600
2531
+ },
2532
+ {
2533
+ "epoch": 9.626666666666667,
2534
+ "grad_norm": 1.336161494255066,
2535
+ "learning_rate": 2.1501903159563688e-08,
2536
+ "loss": 1.5738,
2537
+ "step": 3610
2538
+ },
2539
+ {
2540
+ "epoch": 9.653333333333332,
2541
+ "grad_norm": 0.9720616340637207,
2542
+ "learning_rate": 1.856378737553427e-08,
2543
+ "loss": 1.6266,
2544
+ "step": 3620
2545
+ },
2546
+ {
2547
+ "epoch": 9.68,
2548
+ "grad_norm": 0.8966802358627319,
2549
+ "learning_rate": 1.584067837935327e-08,
2550
+ "loss": 1.6879,
2551
+ "step": 3630
2552
+ },
2553
+ {
2554
+ "epoch": 9.706666666666667,
2555
+ "grad_norm": 1.0030333995819092,
2556
+ "learning_rate": 1.3332812117814731e-08,
2557
+ "loss": 1.6272,
2558
+ "step": 3640
2559
+ },
2560
+ {
2561
+ "epoch": 9.733333333333333,
2562
+ "grad_norm": 0.9756541848182678,
2563
+ "learning_rate": 1.1040405887767503e-08,
2564
+ "loss": 1.6611,
2565
+ "step": 3650
2566
+ },
2567
+ {
2568
+ "epoch": 9.76,
2569
+ "grad_norm": 1.1682424545288086,
2570
+ "learning_rate": 8.963658317286684e-09,
2571
+ "loss": 1.6519,
2572
+ "step": 3660
2573
+ },
2574
+ {
2575
+ "epoch": 9.786666666666667,
2576
+ "grad_norm": 0.93636554479599,
2577
+ "learning_rate": 7.102749348465166e-09,
2578
+ "loss": 1.669,
2579
+ "step": 3670
2580
+ },
2581
+ {
2582
+ "epoch": 9.813333333333333,
2583
+ "grad_norm": 1.0292489528656006,
2584
+ "learning_rate": 5.457840221820831e-09,
2585
+ "loss": 1.5997,
2586
+ "step": 3680
2587
+ },
2588
+ {
2589
+ "epoch": 9.84,
2590
+ "grad_norm": 1.1855809688568115,
2591
+ "learning_rate": 4.029073462325506e-09,
2592
+ "loss": 1.6465,
2593
+ "step": 3690
2594
+ },
2595
+ {
2596
+ "epoch": 9.866666666666667,
2597
+ "grad_norm": 0.9122327566146851,
2598
+ "learning_rate": 2.8165728670573324e-09,
2599
+ "loss": 1.591,
2600
+ "step": 3700
2601
+ },
2602
+ {
2603
+ "epoch": 9.893333333333333,
2604
+ "grad_norm": 1.2053117752075195,
2605
+ "learning_rate": 1.8204434944729676e-09,
2606
+ "loss": 1.6682,
2607
+ "step": 3710
2608
+ },
2609
+ {
2610
+ "epoch": 9.92,
2611
+ "grad_norm": 1.091283917427063,
2612
+ "learning_rate": 1.0407716553040291e-09,
2613
+ "loss": 1.6886,
2614
+ "step": 3720
2615
+ },
2616
+ {
2617
+ "epoch": 9.946666666666667,
2618
+ "grad_norm": 0.9393439292907715,
2619
+ "learning_rate": 4.77624905080576e-10,
2620
+ "loss": 1.5919,
2621
+ "step": 3730
2622
+ },
2623
+ {
2624
+ "epoch": 9.973333333333333,
2625
+ "grad_norm": 1.102495551109314,
2626
+ "learning_rate": 1.3105203827634693e-10,
2627
+ "loss": 1.7873,
2628
+ "step": 3740
2629
+ },
2630
+ {
2631
+ "epoch": 10.0,
2632
+ "grad_norm": 1.1831676959991455,
2633
+ "learning_rate": 1.0830840810327482e-12,
2634
+ "loss": 1.6486,
2635
+ "step": 3750
2636
+ }
2637
+ ],
2638
+ "logging_steps": 10,
2639
+ "max_steps": 3750,
2640
+ "num_input_tokens_seen": 0,
2641
+ "num_train_epochs": 10,
2642
+ "save_steps": 500,
2643
+ "stateful_callbacks": {
2644
+ "TrainerControl": {
2645
+ "args": {
2646
+ "should_epoch_stop": false,
2647
+ "should_evaluate": false,
2648
+ "should_log": false,
2649
+ "should_save": true,
2650
+ "should_training_stop": true
2651
+ },
2652
+ "attributes": {}
2653
+ }
2654
+ },
2655
+ "total_flos": 2.442270942438359e+17,
2656
+ "train_batch_size": 8,
2657
+ "trial_name": null,
2658
+ "trial_params": null
2659
+ }
Direction/Beaver-Danger/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2a9c00fc227fdce226a6e1d78baf7b9dc7392718c01908736a1625727530bd28
3
+ size 5880
Direction/Beaver-Danger/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
Direction/PKURLHF-10K_Safety/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /datas/huggingface/Qwen3-8B
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.15.2
Direction/PKURLHF-10K_Safety/adapter_config.json ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/datas/huggingface/Qwen3-8B",
5
+ "bias": "none",
6
+ "corda_config": null,
7
+ "eva_config": null,
8
+ "exclude_modules": null,
9
+ "fan_in_fan_out": false,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 16,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0.0,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "r": 8,
24
+ "rank_pattern": {},
25
+ "revision": null,
26
+ "target_modules": [
27
+ "v_proj",
28
+ "q_proj",
29
+ "up_proj",
30
+ "gate_proj",
31
+ "k_proj",
32
+ "down_proj",
33
+ "o_proj"
34
+ ],
35
+ "task_type": "CAUSAL_LM",
36
+ "trainable_token_indices": null,
37
+ "use_dora": false,
38
+ "use_rslora": false
39
+ }
Direction/PKURLHF-10K_Safety/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:379899c81f155487b924fdc186c6637795057834e4ae33fb91f8aa59a5c9c03e
3
+ size 87360584
Direction/PKURLHF-10K_Safety/added_tokens.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</think>": 151668,
3
+ "</tool_call>": 151658,
4
+ "</tool_response>": 151666,
5
+ "<think>": 151667,
6
+ "<tool_call>": 151657,
7
+ "<tool_response>": 151665,
8
+ "<|box_end|>": 151649,
9
+ "<|box_start|>": 151648,
10
+ "<|endoftext|>": 151643,
11
+ "<|file_sep|>": 151664,
12
+ "<|fim_middle|>": 151660,
13
+ "<|fim_pad|>": 151662,
14
+ "<|fim_prefix|>": 151659,
15
+ "<|fim_suffix|>": 151661,
16
+ "<|im_end|>": 151645,
17
+ "<|im_start|>": 151644,
18
+ "<|image_pad|>": 151655,
19
+ "<|object_ref_end|>": 151647,
20
+ "<|object_ref_start|>": 151646,
21
+ "<|quad_end|>": 151651,
22
+ "<|quad_start|>": 151650,
23
+ "<|repo_name|>": 151663,
24
+ "<|video_pad|>": 151656,
25
+ "<|vision_end|>": 151653,
26
+ "<|vision_pad|>": 151654,
27
+ "<|vision_start|>": 151652
28
+ }
Direction/PKURLHF-10K_Safety/chat_template.jinja ADDED
@@ -0,0 +1,89 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0].role == 'system' %}
4
+ {{- messages[0].content + '\n\n' }}
5
+ {%- endif %}
6
+ {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
7
+ {%- for tool in tools %}
8
+ {{- "\n" }}
9
+ {{- tool | tojson }}
10
+ {%- endfor %}
11
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
12
+ {%- else %}
13
+ {%- if messages[0].role == 'system' %}
14
+ {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
15
+ {%- endif %}
16
+ {%- endif %}
17
+ {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
18
+ {%- for message in messages[::-1] %}
19
+ {%- set index = (messages|length - 1) - loop.index0 %}
20
+ {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
21
+ {%- set ns.multi_step_tool = false %}
22
+ {%- set ns.last_query_index = index %}
23
+ {%- endif %}
24
+ {%- endfor %}
25
+ {%- for message in messages %}
26
+ {%- if message.content is string %}
27
+ {%- set content = message.content %}
28
+ {%- else %}
29
+ {%- set content = '' %}
30
+ {%- endif %}
31
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
32
+ {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
33
+ {%- elif message.role == "assistant" %}
34
+ {%- set reasoning_content = '' %}
35
+ {%- if message.reasoning_content is string %}
36
+ {%- set reasoning_content = message.reasoning_content %}
37
+ {%- else %}
38
+ {%- if '</think>' in content %}
39
+ {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
40
+ {%- set content = content.split('</think>')[-1].lstrip('\n') %}
41
+ {%- endif %}
42
+ {%- endif %}
43
+ {%- if loop.index0 > ns.last_query_index %}
44
+ {%- if loop.last or (not loop.last and reasoning_content) %}
45
+ {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
46
+ {%- else %}
47
+ {{- '<|im_start|>' + message.role + '\n' + content }}
48
+ {%- endif %}
49
+ {%- else %}
50
+ {{- '<|im_start|>' + message.role + '\n' + content }}
51
+ {%- endif %}
52
+ {%- if message.tool_calls %}
53
+ {%- for tool_call in message.tool_calls %}
54
+ {%- if (loop.first and content) or (not loop.first) %}
55
+ {{- '\n' }}
56
+ {%- endif %}
57
+ {%- if tool_call.function %}
58
+ {%- set tool_call = tool_call.function %}
59
+ {%- endif %}
60
+ {{- '<tool_call>\n{"name": "' }}
61
+ {{- tool_call.name }}
62
+ {{- '", "arguments": ' }}
63
+ {%- if tool_call.arguments is string %}
64
+ {{- tool_call.arguments }}
65
+ {%- else %}
66
+ {{- tool_call.arguments | tojson }}
67
+ {%- endif %}
68
+ {{- '}\n</tool_call>' }}
69
+ {%- endfor %}
70
+ {%- endif %}
71
+ {{- '<|im_end|>\n' }}
72
+ {%- elif message.role == "tool" %}
73
+ {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
74
+ {{- '<|im_start|>user' }}
75
+ {%- endif %}
76
+ {{- '\n<tool_response>\n' }}
77
+ {{- content }}
78
+ {{- '\n</tool_response>' }}
79
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
80
+ {{- '<|im_end|>\n' }}
81
+ {%- endif %}
82
+ {%- endif %}
83
+ {%- endfor %}
84
+ {%- if add_generation_prompt %}
85
+ {{- '<|im_start|>assistant\n' }}
86
+ {%- if enable_thinking is defined and enable_thinking is false %}
87
+ {{- '<think>\n\n</think>\n\n' }}
88
+ {%- endif %}
89
+ {%- endif %}
Direction/PKURLHF-10K_Safety/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
Direction/PKURLHF-10K_Safety/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4b2506283f0c8d04d91a1cb444336a19e1336b1a7ac5ca0f06755c310b6daa62
3
+ size 175012683
Direction/PKURLHF-10K_Safety/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:01f9a0f7843a37be87edd23f4e88aa93b38b95cc2c07503eeb1cf2e4632453a2
3
+ size 14645
Direction/PKURLHF-10K_Safety/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:91da9de8e9bdb9fbad87610906a20f7120bcf6de355ceee649e94c94e3f4ad25
3
+ size 1465
Direction/PKURLHF-10K_Safety/special_tokens_map.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>",
5
+ "<|object_ref_start|>",
6
+ "<|object_ref_end|>",
7
+ "<|box_start|>",
8
+ "<|box_end|>",
9
+ "<|quad_start|>",
10
+ "<|quad_end|>",
11
+ "<|vision_start|>",
12
+ "<|vision_end|>",
13
+ "<|vision_pad|>",
14
+ "<|image_pad|>",
15
+ "<|video_pad|>"
16
+ ],
17
+ "eos_token": {
18
+ "content": "<|im_end|>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ },
24
+ "pad_token": {
25
+ "content": "<|endoftext|>",
26
+ "lstrip": false,
27
+ "normalized": false,
28
+ "rstrip": false,
29
+ "single_word": false
30
+ }
31
+ }
Direction/PKURLHF-10K_Safety/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
3
+ size 11422654
Direction/PKURLHF-10K_Safety/tokenizer_config.json ADDED
@@ -0,0 +1,240 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "151643": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "151644": {
14
+ "content": "<|im_start|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "151645": {
22
+ "content": "<|im_end|>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "151646": {
30
+ "content": "<|object_ref_start|>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "151647": {
38
+ "content": "<|object_ref_end|>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "151648": {
46
+ "content": "<|box_start|>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ },
53
+ "151649": {
54
+ "content": "<|box_end|>",
55
+ "lstrip": false,
56
+ "normalized": false,
57
+ "rstrip": false,
58
+ "single_word": false,
59
+ "special": true
60
+ },
61
+ "151650": {
62
+ "content": "<|quad_start|>",
63
+ "lstrip": false,
64
+ "normalized": false,
65
+ "rstrip": false,
66
+ "single_word": false,
67
+ "special": true
68
+ },
69
+ "151651": {
70
+ "content": "<|quad_end|>",
71
+ "lstrip": false,
72
+ "normalized": false,
73
+ "rstrip": false,
74
+ "single_word": false,
75
+ "special": true
76
+ },
77
+ "151652": {
78
+ "content": "<|vision_start|>",
79
+ "lstrip": false,
80
+ "normalized": false,
81
+ "rstrip": false,
82
+ "single_word": false,
83
+ "special": true
84
+ },
85
+ "151653": {
86
+ "content": "<|vision_end|>",
87
+ "lstrip": false,
88
+ "normalized": false,
89
+ "rstrip": false,
90
+ "single_word": false,
91
+ "special": true
92
+ },
93
+ "151654": {
94
+ "content": "<|vision_pad|>",
95
+ "lstrip": false,
96
+ "normalized": false,
97
+ "rstrip": false,
98
+ "single_word": false,
99
+ "special": true
100
+ },
101
+ "151655": {
102
+ "content": "<|image_pad|>",
103
+ "lstrip": false,
104
+ "normalized": false,
105
+ "rstrip": false,
106
+ "single_word": false,
107
+ "special": true
108
+ },
109
+ "151656": {
110
+ "content": "<|video_pad|>",
111
+ "lstrip": false,
112
+ "normalized": false,
113
+ "rstrip": false,
114
+ "single_word": false,
115
+ "special": true
116
+ },
117
+ "151657": {
118
+ "content": "<tool_call>",
119
+ "lstrip": false,
120
+ "normalized": false,
121
+ "rstrip": false,
122
+ "single_word": false,
123
+ "special": false
124
+ },
125
+ "151658": {
126
+ "content": "</tool_call>",
127
+ "lstrip": false,
128
+ "normalized": false,
129
+ "rstrip": false,
130
+ "single_word": false,
131
+ "special": false
132
+ },
133
+ "151659": {
134
+ "content": "<|fim_prefix|>",
135
+ "lstrip": false,
136
+ "normalized": false,
137
+ "rstrip": false,
138
+ "single_word": false,
139
+ "special": false
140
+ },
141
+ "151660": {
142
+ "content": "<|fim_middle|>",
143
+ "lstrip": false,
144
+ "normalized": false,
145
+ "rstrip": false,
146
+ "single_word": false,
147
+ "special": false
148
+ },
149
+ "151661": {
150
+ "content": "<|fim_suffix|>",
151
+ "lstrip": false,
152
+ "normalized": false,
153
+ "rstrip": false,
154
+ "single_word": false,
155
+ "special": false
156
+ },
157
+ "151662": {
158
+ "content": "<|fim_pad|>",
159
+ "lstrip": false,
160
+ "normalized": false,
161
+ "rstrip": false,
162
+ "single_word": false,
163
+ "special": false
164
+ },
165
+ "151663": {
166
+ "content": "<|repo_name|>",
167
+ "lstrip": false,
168
+ "normalized": false,
169
+ "rstrip": false,
170
+ "single_word": false,
171
+ "special": false
172
+ },
173
+ "151664": {
174
+ "content": "<|file_sep|>",
175
+ "lstrip": false,
176
+ "normalized": false,
177
+ "rstrip": false,
178
+ "single_word": false,
179
+ "special": false
180
+ },
181
+ "151665": {
182
+ "content": "<tool_response>",
183
+ "lstrip": false,
184
+ "normalized": false,
185
+ "rstrip": false,
186
+ "single_word": false,
187
+ "special": false
188
+ },
189
+ "151666": {
190
+ "content": "</tool_response>",
191
+ "lstrip": false,
192
+ "normalized": false,
193
+ "rstrip": false,
194
+ "single_word": false,
195
+ "special": false
196
+ },
197
+ "151667": {
198
+ "content": "<think>",
199
+ "lstrip": false,
200
+ "normalized": false,
201
+ "rstrip": false,
202
+ "single_word": false,
203
+ "special": false
204
+ },
205
+ "151668": {
206
+ "content": "</think>",
207
+ "lstrip": false,
208
+ "normalized": false,
209
+ "rstrip": false,
210
+ "single_word": false,
211
+ "special": false
212
+ }
213
+ },
214
+ "additional_special_tokens": [
215
+ "<|im_start|>",
216
+ "<|im_end|>",
217
+ "<|object_ref_start|>",
218
+ "<|object_ref_end|>",
219
+ "<|box_start|>",
220
+ "<|box_end|>",
221
+ "<|quad_start|>",
222
+ "<|quad_end|>",
223
+ "<|vision_start|>",
224
+ "<|vision_end|>",
225
+ "<|vision_pad|>",
226
+ "<|image_pad|>",
227
+ "<|video_pad|>"
228
+ ],
229
+ "bos_token": null,
230
+ "clean_up_tokenization_spaces": false,
231
+ "eos_token": "<|im_end|>",
232
+ "errors": "replace",
233
+ "extra_special_tokens": {},
234
+ "model_max_length": 131072,
235
+ "pad_token": "<|endoftext|>",
236
+ "padding_side": "right",
237
+ "split_special_tokens": false,
238
+ "tokenizer_class": "Qwen2Tokenizer",
239
+ "unk_token": null
240
+ }
Direction/PKURLHF-10K_Safety/trainer_state.json ADDED
The diff for this file is too large to render. See raw diff
 
Direction/PKURLHF-10K_Safety/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c50dc44de7f4ac5941a9f80302f3613586626bba2cfc7aae255c69e4a3432eec
3
+ size 6225
Direction/PKURLHF-10K_Safety/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
README.md CHANGED
@@ -1,3 +1,46 @@
1
- ---
2
- license: apache-2.0
3
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ## Introduction
2
+
3
+ This repository provides the weight files required for computing sample-level **SQSD** scores based on **Qwen3-8B**, as used in the paper **"From Parameter Dynamics to Risk Scoring: Quantifying Sample-Level Safety Degradation in LLM Fine-tuning"**.
4
+
5
+ Two types of weights are needed to compute **SQSD**:
6
+
7
+ - **Parameter shift direction weights (Direction)**: Encode safety-relevant directions in the model's parameter space, used to measure how individual fine-tuning samples affect model safety.
8
+ - **Model initialization weights (initial-state)**: Serve as the starting point for SQSD computation. **Note**: These weights are only required when computing **Danger-Projection**. For details, please refer to **Section 4.3 Parameter Initialization** of the paper.
9
+
10
+ ## Links
11
+
12
+ - Paper: https://arxiv.org/abs/2605.04572
13
+ - GitHub: https://github.com/Jason-wx/SQSD
14
+
15
+ ## Directory Structure
16
+
17
+ ```
18
+ hf_upload/
19
+ ├── Direction/ # Parameter shift direction weights
20
+ │ ├── Ageis_Danger/ # Danger direction weights
21
+ │ ├── Beaver-Danger/ # Danger direction weights
22
+ │ └── PKURLHF-10K_Safety/ # Safety direction weights
23
+ ├── initial-state/ # Model initialization weights
24
+ │ └── dolly_ckpt_5850/ # Initial weights (initialized via Danger-Projection)
25
+ └── README.md
26
+ ```
27
+
28
+ ## Direction Folder
29
+
30
+ The Direction folder contains three sets of direction weights, each extracted from a different dataset, encoding either a safety or danger direction in parameter space:
31
+
32
+ | Name | Type | Description |
33
+ |------|------|-------------|
34
+ | Ageis_Danger | Danger | Danger direction weights extracted from the Aegis dataset |
35
+ | Beaver-Danger | Danger | Danger direction weights extracted from the BeaverTails dataset |
36
+ | PKURLHF-10K_Safety | Safety | Safety direction weights extracted from the PKU-RLHF dataset |
37
+
38
+ These direction weights encode safety-relevant parameter shift directions and are a core dependency for computing SQSD scores.
39
+
40
+ ## initial-state Folder
41
+
42
+ The weights in `initial-state` (`dolly_ckpt_5850`) represent the model initialization state derived via the **Danger-Projection** method — specifically, the parameter point obtained by projecting the base model weights along the danger direction. This serves as the reference starting point for subsequent SQSD computation.
43
+
44
+ > ⚠️ The paper defines two initialization strategies depending on the projection direction (see **Section 4.3 Parameter Initialization**):
45
+ > - **Danger direction** (drift-enhanced sensitivity): θ_initial = θ_t, initialized from a fine-tuning checkpoint that exhibits high directional sensitivity. The weights provided here (`dolly_ckpt_5850`) serve this purpose.
46
+ > - **Safety direction** (linear-path sensitivity): θ_initial = θ_0 + α\*V_safety, initialized by interpolating from the base model along the safety direction vector. **No additional checkpoint is required** — only the base model weights and the safety direction weights from the `Direction` folder are needed.
initial-state/dolly_ckpt_5850/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /datas/huggingface/Qwen3-8B
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.15.2
initial-state/dolly_ckpt_5850/adapter_config.json ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/datas/huggingface/Qwen3-8B",
5
+ "bias": "none",
6
+ "corda_config": null,
7
+ "eva_config": null,
8
+ "exclude_modules": null,
9
+ "fan_in_fan_out": false,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 16,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0.0,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "r": 8,
24
+ "rank_pattern": {},
25
+ "revision": null,
26
+ "target_modules": [
27
+ "down_proj",
28
+ "gate_proj",
29
+ "o_proj",
30
+ "q_proj",
31
+ "v_proj",
32
+ "up_proj",
33
+ "k_proj"
34
+ ],
35
+ "task_type": "CAUSAL_LM",
36
+ "trainable_token_indices": null,
37
+ "use_dora": false,
38
+ "use_rslora": false
39
+ }
initial-state/dolly_ckpt_5850/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1bc3091a9232876ccb3178f80a6f4db587910dbd5d06f68a1c35ad8f9c1c5563
3
+ size 87360584
initial-state/dolly_ckpt_5850/added_tokens.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</think>": 151668,
3
+ "</tool_call>": 151658,
4
+ "</tool_response>": 151666,
5
+ "<think>": 151667,
6
+ "<tool_call>": 151657,
7
+ "<tool_response>": 151665,
8
+ "<|box_end|>": 151649,
9
+ "<|box_start|>": 151648,
10
+ "<|endoftext|>": 151643,
11
+ "<|file_sep|>": 151664,
12
+ "<|fim_middle|>": 151660,
13
+ "<|fim_pad|>": 151662,
14
+ "<|fim_prefix|>": 151659,
15
+ "<|fim_suffix|>": 151661,
16
+ "<|im_end|>": 151645,
17
+ "<|im_start|>": 151644,
18
+ "<|image_pad|>": 151655,
19
+ "<|object_ref_end|>": 151647,
20
+ "<|object_ref_start|>": 151646,
21
+ "<|quad_end|>": 151651,
22
+ "<|quad_start|>": 151650,
23
+ "<|repo_name|>": 151663,
24
+ "<|video_pad|>": 151656,
25
+ "<|vision_end|>": 151653,
26
+ "<|vision_pad|>": 151654,
27
+ "<|vision_start|>": 151652
28
+ }
initial-state/dolly_ckpt_5850/chat_template.jinja ADDED
@@ -0,0 +1,89 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0].role == 'system' %}
4
+ {{- messages[0].content + '\n\n' }}
5
+ {%- endif %}
6
+ {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
7
+ {%- for tool in tools %}
8
+ {{- "\n" }}
9
+ {{- tool | tojson }}
10
+ {%- endfor %}
11
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
12
+ {%- else %}
13
+ {%- if messages[0].role == 'system' %}
14
+ {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
15
+ {%- endif %}
16
+ {%- endif %}
17
+ {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
18
+ {%- for message in messages[::-1] %}
19
+ {%- set index = (messages|length - 1) - loop.index0 %}
20
+ {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
21
+ {%- set ns.multi_step_tool = false %}
22
+ {%- set ns.last_query_index = index %}
23
+ {%- endif %}
24
+ {%- endfor %}
25
+ {%- for message in messages %}
26
+ {%- if message.content is string %}
27
+ {%- set content = message.content %}
28
+ {%- else %}
29
+ {%- set content = '' %}
30
+ {%- endif %}
31
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
32
+ {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
33
+ {%- elif message.role == "assistant" %}
34
+ {%- set reasoning_content = '' %}
35
+ {%- if message.reasoning_content is string %}
36
+ {%- set reasoning_content = message.reasoning_content %}
37
+ {%- else %}
38
+ {%- if '</think>' in content %}
39
+ {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
40
+ {%- set content = content.split('</think>')[-1].lstrip('\n') %}
41
+ {%- endif %}
42
+ {%- endif %}
43
+ {%- if loop.index0 > ns.last_query_index %}
44
+ {%- if loop.last or (not loop.last and reasoning_content) %}
45
+ {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
46
+ {%- else %}
47
+ {{- '<|im_start|>' + message.role + '\n' + content }}
48
+ {%- endif %}
49
+ {%- else %}
50
+ {{- '<|im_start|>' + message.role + '\n' + content }}
51
+ {%- endif %}
52
+ {%- if message.tool_calls %}
53
+ {%- for tool_call in message.tool_calls %}
54
+ {%- if (loop.first and content) or (not loop.first) %}
55
+ {{- '\n' }}
56
+ {%- endif %}
57
+ {%- if tool_call.function %}
58
+ {%- set tool_call = tool_call.function %}
59
+ {%- endif %}
60
+ {{- '<tool_call>\n{"name": "' }}
61
+ {{- tool_call.name }}
62
+ {{- '", "arguments": ' }}
63
+ {%- if tool_call.arguments is string %}
64
+ {{- tool_call.arguments }}
65
+ {%- else %}
66
+ {{- tool_call.arguments | tojson }}
67
+ {%- endif %}
68
+ {{- '}\n</tool_call>' }}
69
+ {%- endfor %}
70
+ {%- endif %}
71
+ {{- '<|im_end|>\n' }}
72
+ {%- elif message.role == "tool" %}
73
+ {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
74
+ {{- '<|im_start|>user' }}
75
+ {%- endif %}
76
+ {{- '\n<tool_response>\n' }}
77
+ {{- content }}
78
+ {{- '\n</tool_response>' }}
79
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
80
+ {{- '<|im_end|>\n' }}
81
+ {%- endif %}
82
+ {%- endif %}
83
+ {%- endfor %}
84
+ {%- if add_generation_prompt %}
85
+ {{- '<|im_start|>assistant\n' }}
86
+ {%- if enable_thinking is defined and enable_thinking is false %}
87
+ {{- '<think>\n\n</think>\n\n' }}
88
+ {%- endif %}
89
+ {%- endif %}
initial-state/dolly_ckpt_5850/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
initial-state/dolly_ckpt_5850/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6af0d5ba04007eaac0243d7edd05961fb86105689ed8cf59c5fec806d9816cef
3
+ size 175012683
initial-state/dolly_ckpt_5850/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c8707ffebfdb9126b866080be7f7c305b76f99b38d4f05102f060b97c427f18c
3
+ size 14645
initial-state/dolly_ckpt_5850/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ae1b709f0013d3dc90d317a90857e87d052caed139bc77cec5ca4ccd7ebe2b80
3
+ size 1465