Yinxing commited on
Commit
0075175
·
1 Parent(s): bf4a1c9

Upload 12 files

Browse files
lora_li_V5/checkpoint-350/README.md ADDED
@@ -0,0 +1,207 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: line-corporation/japanese-large-lm-3.6b
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
+ - **Shared by [optional]:** [More Information Needed]
22
+ - **Model type:** [More Information Needed]
23
+ - **Language(s) (NLP):** [More Information Needed]
24
+ - **License:** [More Information Needed]
25
+ - **Finetuned from model [optional]:** [More Information Needed]
26
+
27
+ ### Model Sources [optional]
28
+
29
+ <!-- Provide the basic links for the model. -->
30
+
31
+ - **Repository:** [More Information Needed]
32
+ - **Paper [optional]:** [More Information Needed]
33
+ - **Demo [optional]:** [More Information Needed]
34
+
35
+ ## Uses
36
+
37
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
38
+
39
+ ### Direct Use
40
+
41
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
42
+
43
+ [More Information Needed]
44
+
45
+ ### Downstream Use [optional]
46
+
47
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
48
+
49
+ [More Information Needed]
50
+
51
+ ### Out-of-Scope Use
52
+
53
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
54
+
55
+ [More Information Needed]
56
+
57
+ ## Bias, Risks, and Limitations
58
+
59
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
60
+
61
+ [More Information Needed]
62
+
63
+ ### Recommendations
64
+
65
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
66
+
67
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
68
+
69
+ ## How to Get Started with the Model
70
+
71
+ Use the code below to get started with the model.
72
+
73
+ [More Information Needed]
74
+
75
+ ## Training Details
76
+
77
+ ### Training Data
78
+
79
+ <!-- This should link to a Data 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. -->
80
+
81
+ [More Information Needed]
82
+
83
+ ### Training Procedure
84
+
85
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
86
+
87
+ #### Preprocessing [optional]
88
+
89
+ [More Information Needed]
90
+
91
+
92
+ #### Training Hyperparameters
93
+
94
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
95
+
96
+ #### Speeds, Sizes, Times [optional]
97
+
98
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
99
+
100
+ [More Information Needed]
101
+
102
+ ## Evaluation
103
+
104
+ <!-- This section describes the evaluation protocols and provides the results. -->
105
+
106
+ ### Testing Data, Factors & Metrics
107
+
108
+ #### Testing Data
109
+
110
+ <!-- This should link to a Data Card if possible. -->
111
+
112
+ [More Information Needed]
113
+
114
+ #### Factors
115
+
116
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
117
+
118
+ [More Information Needed]
119
+
120
+ #### Metrics
121
+
122
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
123
+
124
+ [More Information Needed]
125
+
126
+ ### Results
127
+
128
+ [More Information Needed]
129
+
130
+ #### Summary
131
+
132
+
133
+
134
+ ## Model Examination [optional]
135
+
136
+ <!-- Relevant interpretability work for the model goes here -->
137
+
138
+ [More Information Needed]
139
+
140
+ ## Environmental Impact
141
+
142
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
143
+
144
+ 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).
145
+
146
+ - **Hardware Type:** [More Information Needed]
147
+ - **Hours used:** [More Information Needed]
148
+ - **Cloud Provider:** [More Information Needed]
149
+ - **Compute Region:** [More Information Needed]
150
+ - **Carbon Emitted:** [More Information Needed]
151
+
152
+ ## Technical Specifications [optional]
153
+
154
+ ### Model Architecture and Objective
155
+
156
+ [More Information Needed]
157
+
158
+ ### Compute Infrastructure
159
+
160
+ [More Information Needed]
161
+
162
+ #### Hardware
163
+
164
+ [More Information Needed]
165
+
166
+ #### Software
167
+
168
+ [More Information Needed]
169
+
170
+ ## Citation [optional]
171
+
172
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
173
+
174
+ **BibTeX:**
175
+
176
+ [More Information Needed]
177
+
178
+ **APA:**
179
+
180
+ [More Information Needed]
181
+
182
+ ## Glossary [optional]
183
+
184
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
185
+
186
+ [More Information Needed]
187
+
188
+ ## More Information [optional]
189
+
190
+ [More Information Needed]
191
+
192
+ ## Model Card Authors [optional]
193
+
194
+ [More Information Needed]
195
+
196
+ ## Model Card Contact
197
+
198
+ [More Information Needed]
199
+
200
+
201
+ ## Training procedure
202
+
203
+
204
+ ### Framework versions
205
+
206
+
207
+ - PEFT 0.6.2
lora_li_V5/checkpoint-350/adapter_config.json ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "line-corporation/japanese-large-lm-3.6b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "lora_alpha": 8,
12
+ "lora_dropout": 0.05,
13
+ "modules_to_save": null,
14
+ "peft_type": "LORA",
15
+ "r": 24,
16
+ "rank_pattern": {},
17
+ "revision": null,
18
+ "target_modules": [
19
+ "dense",
20
+ "query_key_value"
21
+ ],
22
+ "task_type": "CAUSAL_LM"
23
+ }
lora_li_V5/checkpoint-350/adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:293e8c7388b1d61f4c5c32375b64fe91c39c48fe5fa3af824f4d077776420d34
3
+ size 53128554
lora_li_V5/checkpoint-350/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1a3049363307409363c67a1ecccf6474acc2df025acac8fb4ca8ee6b358f1ef5
3
+ size 26730618
lora_li_V5/checkpoint-350/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8581e8b68dc6c6196afee9e66ea321c280a0753f1cbf05a1d267b0cbec773f1e
3
+ size 14244
lora_li_V5/checkpoint-350/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1f9945ea8e74b658f882c54c4765f842ed7997c3e0788b118d20f344f68ad639
3
+ size 1064
lora_li_V5/checkpoint-350/special_tokens_map.json ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": "<s>",
3
+ "cls_token": "<cls>",
4
+ "eos_token": "</s>",
5
+ "mask_token": "<mask>",
6
+ "pad_token": "<pad>",
7
+ "sep_token": "<sep>",
8
+ "unk_token": "<unk>"
9
+ }
lora_li_V5/checkpoint-350/spiece.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0c5c56a739832923347681ed8a03a9cbf5afb6d1fe60089a5b01dd2dd063ab71
3
+ size 1208648
lora_li_V5/checkpoint-350/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
lora_li_V5/checkpoint-350/tokenizer_config.json ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": null,
3
+ "bos_token": "<s>",
4
+ "clean_up_tokenization_spaces": true,
5
+ "cls_token": "<cls>",
6
+ "do_lower_case": false,
7
+ "eos_token": "</s>",
8
+ "extra_ids": 0,
9
+ "keep_accents": true,
10
+ "legacy": true,
11
+ "mask_token": "<mask>",
12
+ "model_max_length": 1000000000000000019884624838656,
13
+ "pad_token": "<pad>",
14
+ "sep_token": "<sep>",
15
+ "sp_model_kwargs": {},
16
+ "tokenizer_class": "T5Tokenizer",
17
+ "unk_token": "<unk>"
18
+ }
lora_li_V5/checkpoint-350/trainer_state.json ADDED
@@ -0,0 +1,999 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 7.0,
5
+ "eval_steps": 5,
6
+ "global_step": 350,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.1,
13
+ "learning_rate": 1.6666666666666667e-05,
14
+ "loss": 3.7048,
15
+ "step": 5
16
+ },
17
+ {
18
+ "epoch": 0.1,
19
+ "eval_loss": 3.791994571685791,
20
+ "eval_runtime": 4.4098,
21
+ "eval_samples_per_second": 45.354,
22
+ "eval_steps_per_second": 5.669,
23
+ "step": 5
24
+ },
25
+ {
26
+ "epoch": 0.2,
27
+ "learning_rate": 3.3333333333333335e-05,
28
+ "loss": 3.8064,
29
+ "step": 10
30
+ },
31
+ {
32
+ "epoch": 0.2,
33
+ "eval_loss": 3.777104377746582,
34
+ "eval_runtime": 4.422,
35
+ "eval_samples_per_second": 45.229,
36
+ "eval_steps_per_second": 5.654,
37
+ "step": 10
38
+ },
39
+ {
40
+ "epoch": 0.3,
41
+ "learning_rate": 5e-05,
42
+ "loss": 3.7275,
43
+ "step": 15
44
+ },
45
+ {
46
+ "epoch": 0.3,
47
+ "eval_loss": 3.733438014984131,
48
+ "eval_runtime": 4.4275,
49
+ "eval_samples_per_second": 45.172,
50
+ "eval_steps_per_second": 5.646,
51
+ "step": 15
52
+ },
53
+ {
54
+ "epoch": 0.4,
55
+ "learning_rate": 6.666666666666667e-05,
56
+ "loss": 3.7422,
57
+ "step": 20
58
+ },
59
+ {
60
+ "epoch": 0.4,
61
+ "eval_loss": 3.6596221923828125,
62
+ "eval_runtime": 4.4331,
63
+ "eval_samples_per_second": 45.115,
64
+ "eval_steps_per_second": 5.639,
65
+ "step": 20
66
+ },
67
+ {
68
+ "epoch": 0.5,
69
+ "learning_rate": 8.333333333333334e-05,
70
+ "loss": 3.637,
71
+ "step": 25
72
+ },
73
+ {
74
+ "epoch": 0.5,
75
+ "eval_loss": 3.5282764434814453,
76
+ "eval_runtime": 4.4412,
77
+ "eval_samples_per_second": 45.033,
78
+ "eval_steps_per_second": 5.629,
79
+ "step": 25
80
+ },
81
+ {
82
+ "epoch": 0.6,
83
+ "learning_rate": 0.0001,
84
+ "loss": 3.4441,
85
+ "step": 30
86
+ },
87
+ {
88
+ "epoch": 0.6,
89
+ "eval_loss": 3.320693254470825,
90
+ "eval_runtime": 4.4455,
91
+ "eval_samples_per_second": 44.99,
92
+ "eval_steps_per_second": 5.624,
93
+ "step": 30
94
+ },
95
+ {
96
+ "epoch": 0.7,
97
+ "learning_rate": 9.948453608247423e-05,
98
+ "loss": 3.2032,
99
+ "step": 35
100
+ },
101
+ {
102
+ "epoch": 0.7,
103
+ "eval_loss": 3.0499627590179443,
104
+ "eval_runtime": 4.4488,
105
+ "eval_samples_per_second": 44.956,
106
+ "eval_steps_per_second": 5.619,
107
+ "step": 35
108
+ },
109
+ {
110
+ "epoch": 0.8,
111
+ "learning_rate": 9.896907216494846e-05,
112
+ "loss": 2.8873,
113
+ "step": 40
114
+ },
115
+ {
116
+ "epoch": 0.8,
117
+ "eval_loss": 2.7090697288513184,
118
+ "eval_runtime": 4.4542,
119
+ "eval_samples_per_second": 44.902,
120
+ "eval_steps_per_second": 5.613,
121
+ "step": 40
122
+ },
123
+ {
124
+ "epoch": 0.9,
125
+ "learning_rate": 9.845360824742269e-05,
126
+ "loss": 2.5119,
127
+ "step": 45
128
+ },
129
+ {
130
+ "epoch": 0.9,
131
+ "eval_loss": 2.2660412788391113,
132
+ "eval_runtime": 4.4547,
133
+ "eval_samples_per_second": 44.896,
134
+ "eval_steps_per_second": 5.612,
135
+ "step": 45
136
+ },
137
+ {
138
+ "epoch": 1.0,
139
+ "learning_rate": 9.793814432989691e-05,
140
+ "loss": 1.8782,
141
+ "step": 50
142
+ },
143
+ {
144
+ "epoch": 1.0,
145
+ "eval_loss": 1.9092340469360352,
146
+ "eval_runtime": 4.4568,
147
+ "eval_samples_per_second": 44.876,
148
+ "eval_steps_per_second": 5.609,
149
+ "step": 50
150
+ },
151
+ {
152
+ "epoch": 1.1,
153
+ "learning_rate": 9.742268041237114e-05,
154
+ "loss": 1.9562,
155
+ "step": 55
156
+ },
157
+ {
158
+ "epoch": 1.1,
159
+ "eval_loss": 1.6684613227844238,
160
+ "eval_runtime": 4.458,
161
+ "eval_samples_per_second": 44.863,
162
+ "eval_steps_per_second": 5.608,
163
+ "step": 55
164
+ },
165
+ {
166
+ "epoch": 1.2,
167
+ "learning_rate": 9.690721649484537e-05,
168
+ "loss": 1.4385,
169
+ "step": 60
170
+ },
171
+ {
172
+ "epoch": 1.2,
173
+ "eval_loss": 1.4644845724105835,
174
+ "eval_runtime": 4.4554,
175
+ "eval_samples_per_second": 44.889,
176
+ "eval_steps_per_second": 5.611,
177
+ "step": 60
178
+ },
179
+ {
180
+ "epoch": 1.3,
181
+ "learning_rate": 9.639175257731959e-05,
182
+ "loss": 1.4579,
183
+ "step": 65
184
+ },
185
+ {
186
+ "epoch": 1.3,
187
+ "eval_loss": 1.323061227798462,
188
+ "eval_runtime": 4.4568,
189
+ "eval_samples_per_second": 44.875,
190
+ "eval_steps_per_second": 5.609,
191
+ "step": 65
192
+ },
193
+ {
194
+ "epoch": 1.4,
195
+ "learning_rate": 9.587628865979382e-05,
196
+ "loss": 1.2973,
197
+ "step": 70
198
+ },
199
+ {
200
+ "epoch": 1.4,
201
+ "eval_loss": 1.296040654182434,
202
+ "eval_runtime": 4.4572,
203
+ "eval_samples_per_second": 44.871,
204
+ "eval_steps_per_second": 5.609,
205
+ "step": 70
206
+ },
207
+ {
208
+ "epoch": 1.5,
209
+ "learning_rate": 9.536082474226805e-05,
210
+ "loss": 1.0638,
211
+ "step": 75
212
+ },
213
+ {
214
+ "epoch": 1.5,
215
+ "eval_loss": 1.2820910215377808,
216
+ "eval_runtime": 4.4578,
217
+ "eval_samples_per_second": 44.865,
218
+ "eval_steps_per_second": 5.608,
219
+ "step": 75
220
+ },
221
+ {
222
+ "epoch": 1.6,
223
+ "learning_rate": 9.484536082474227e-05,
224
+ "loss": 1.3853,
225
+ "step": 80
226
+ },
227
+ {
228
+ "epoch": 1.6,
229
+ "eval_loss": 1.273141622543335,
230
+ "eval_runtime": 4.4582,
231
+ "eval_samples_per_second": 44.861,
232
+ "eval_steps_per_second": 5.608,
233
+ "step": 80
234
+ },
235
+ {
236
+ "epoch": 1.7,
237
+ "learning_rate": 9.43298969072165e-05,
238
+ "loss": 0.9734,
239
+ "step": 85
240
+ },
241
+ {
242
+ "epoch": 1.7,
243
+ "eval_loss": 1.2661323547363281,
244
+ "eval_runtime": 4.4571,
245
+ "eval_samples_per_second": 44.873,
246
+ "eval_steps_per_second": 5.609,
247
+ "step": 85
248
+ },
249
+ {
250
+ "epoch": 1.8,
251
+ "learning_rate": 9.381443298969073e-05,
252
+ "loss": 1.4012,
253
+ "step": 90
254
+ },
255
+ {
256
+ "epoch": 1.8,
257
+ "eval_loss": 1.2609992027282715,
258
+ "eval_runtime": 4.4568,
259
+ "eval_samples_per_second": 44.875,
260
+ "eval_steps_per_second": 5.609,
261
+ "step": 90
262
+ },
263
+ {
264
+ "epoch": 1.9,
265
+ "learning_rate": 9.329896907216495e-05,
266
+ "loss": 1.1392,
267
+ "step": 95
268
+ },
269
+ {
270
+ "epoch": 1.9,
271
+ "eval_loss": 1.2571262121200562,
272
+ "eval_runtime": 4.4597,
273
+ "eval_samples_per_second": 44.846,
274
+ "eval_steps_per_second": 5.606,
275
+ "step": 95
276
+ },
277
+ {
278
+ "epoch": 2.0,
279
+ "learning_rate": 9.278350515463918e-05,
280
+ "loss": 0.9244,
281
+ "step": 100
282
+ },
283
+ {
284
+ "epoch": 2.0,
285
+ "eval_loss": 1.2540690898895264,
286
+ "eval_runtime": 4.458,
287
+ "eval_samples_per_second": 44.864,
288
+ "eval_steps_per_second": 5.608,
289
+ "step": 100
290
+ },
291
+ {
292
+ "epoch": 2.1,
293
+ "learning_rate": 9.22680412371134e-05,
294
+ "loss": 1.521,
295
+ "step": 105
296
+ },
297
+ {
298
+ "epoch": 2.1,
299
+ "eval_loss": 1.2517199516296387,
300
+ "eval_runtime": 4.4571,
301
+ "eval_samples_per_second": 44.872,
302
+ "eval_steps_per_second": 5.609,
303
+ "step": 105
304
+ },
305
+ {
306
+ "epoch": 2.2,
307
+ "learning_rate": 9.175257731958763e-05,
308
+ "loss": 1.0514,
309
+ "step": 110
310
+ },
311
+ {
312
+ "epoch": 2.2,
313
+ "eval_loss": 1.2495222091674805,
314
+ "eval_runtime": 4.4586,
315
+ "eval_samples_per_second": 44.857,
316
+ "eval_steps_per_second": 5.607,
317
+ "step": 110
318
+ },
319
+ {
320
+ "epoch": 2.3,
321
+ "learning_rate": 9.123711340206186e-05,
322
+ "loss": 1.2462,
323
+ "step": 115
324
+ },
325
+ {
326
+ "epoch": 2.3,
327
+ "eval_loss": 1.2475061416625977,
328
+ "eval_runtime": 4.4596,
329
+ "eval_samples_per_second": 44.848,
330
+ "eval_steps_per_second": 5.606,
331
+ "step": 115
332
+ },
333
+ {
334
+ "epoch": 2.4,
335
+ "learning_rate": 9.072164948453609e-05,
336
+ "loss": 1.1681,
337
+ "step": 120
338
+ },
339
+ {
340
+ "epoch": 2.4,
341
+ "eval_loss": 1.2455750703811646,
342
+ "eval_runtime": 4.46,
343
+ "eval_samples_per_second": 44.843,
344
+ "eval_steps_per_second": 5.605,
345
+ "step": 120
346
+ },
347
+ {
348
+ "epoch": 2.5,
349
+ "learning_rate": 9.020618556701031e-05,
350
+ "loss": 1.0076,
351
+ "step": 125
352
+ },
353
+ {
354
+ "epoch": 2.5,
355
+ "eval_loss": 1.2440249919891357,
356
+ "eval_runtime": 4.4586,
357
+ "eval_samples_per_second": 44.857,
358
+ "eval_steps_per_second": 5.607,
359
+ "step": 125
360
+ },
361
+ {
362
+ "epoch": 2.6,
363
+ "learning_rate": 8.969072164948454e-05,
364
+ "loss": 1.4385,
365
+ "step": 130
366
+ },
367
+ {
368
+ "epoch": 2.6,
369
+ "eval_loss": 1.2428377866744995,
370
+ "eval_runtime": 4.4618,
371
+ "eval_samples_per_second": 44.825,
372
+ "eval_steps_per_second": 5.603,
373
+ "step": 130
374
+ },
375
+ {
376
+ "epoch": 2.7,
377
+ "learning_rate": 8.917525773195877e-05,
378
+ "loss": 0.9315,
379
+ "step": 135
380
+ },
381
+ {
382
+ "epoch": 2.7,
383
+ "eval_loss": 1.241697907447815,
384
+ "eval_runtime": 4.4589,
385
+ "eval_samples_per_second": 44.855,
386
+ "eval_steps_per_second": 5.607,
387
+ "step": 135
388
+ },
389
+ {
390
+ "epoch": 2.8,
391
+ "learning_rate": 8.865979381443299e-05,
392
+ "loss": 1.3113,
393
+ "step": 140
394
+ },
395
+ {
396
+ "epoch": 2.8,
397
+ "eval_loss": 1.240850567817688,
398
+ "eval_runtime": 4.4585,
399
+ "eval_samples_per_second": 44.859,
400
+ "eval_steps_per_second": 5.607,
401
+ "step": 140
402
+ },
403
+ {
404
+ "epoch": 2.9,
405
+ "learning_rate": 8.814432989690722e-05,
406
+ "loss": 1.1529,
407
+ "step": 145
408
+ },
409
+ {
410
+ "epoch": 2.9,
411
+ "eval_loss": 1.2396690845489502,
412
+ "eval_runtime": 4.4584,
413
+ "eval_samples_per_second": 44.859,
414
+ "eval_steps_per_second": 5.607,
415
+ "step": 145
416
+ },
417
+ {
418
+ "epoch": 3.0,
419
+ "learning_rate": 8.762886597938145e-05,
420
+ "loss": 0.919,
421
+ "step": 150
422
+ },
423
+ {
424
+ "epoch": 3.0,
425
+ "eval_loss": 1.238713264465332,
426
+ "eval_runtime": 4.4607,
427
+ "eval_samples_per_second": 44.836,
428
+ "eval_steps_per_second": 5.604,
429
+ "step": 150
430
+ },
431
+ {
432
+ "epoch": 3.1,
433
+ "learning_rate": 8.711340206185567e-05,
434
+ "loss": 1.4306,
435
+ "step": 155
436
+ },
437
+ {
438
+ "epoch": 3.1,
439
+ "eval_loss": 1.2377328872680664,
440
+ "eval_runtime": 4.4589,
441
+ "eval_samples_per_second": 44.854,
442
+ "eval_steps_per_second": 5.607,
443
+ "step": 155
444
+ },
445
+ {
446
+ "epoch": 3.2,
447
+ "learning_rate": 8.65979381443299e-05,
448
+ "loss": 0.9846,
449
+ "step": 160
450
+ },
451
+ {
452
+ "epoch": 3.2,
453
+ "eval_loss": 1.2368167638778687,
454
+ "eval_runtime": 4.4586,
455
+ "eval_samples_per_second": 44.857,
456
+ "eval_steps_per_second": 5.607,
457
+ "step": 160
458
+ },
459
+ {
460
+ "epoch": 3.3,
461
+ "learning_rate": 8.608247422680413e-05,
462
+ "loss": 1.2453,
463
+ "step": 165
464
+ },
465
+ {
466
+ "epoch": 3.3,
467
+ "eval_loss": 1.2363089323043823,
468
+ "eval_runtime": 4.4577,
469
+ "eval_samples_per_second": 44.866,
470
+ "eval_steps_per_second": 5.608,
471
+ "step": 165
472
+ },
473
+ {
474
+ "epoch": 3.4,
475
+ "learning_rate": 8.556701030927835e-05,
476
+ "loss": 1.1861,
477
+ "step": 170
478
+ },
479
+ {
480
+ "epoch": 3.4,
481
+ "eval_loss": 1.235287070274353,
482
+ "eval_runtime": 4.458,
483
+ "eval_samples_per_second": 44.863,
484
+ "eval_steps_per_second": 5.608,
485
+ "step": 170
486
+ },
487
+ {
488
+ "epoch": 3.5,
489
+ "learning_rate": 8.505154639175259e-05,
490
+ "loss": 0.9753,
491
+ "step": 175
492
+ },
493
+ {
494
+ "epoch": 3.5,
495
+ "eval_loss": 1.2343323230743408,
496
+ "eval_runtime": 4.5175,
497
+ "eval_samples_per_second": 44.272,
498
+ "eval_steps_per_second": 5.534,
499
+ "step": 175
500
+ },
501
+ {
502
+ "epoch": 3.6,
503
+ "learning_rate": 8.453608247422681e-05,
504
+ "loss": 1.3656,
505
+ "step": 180
506
+ },
507
+ {
508
+ "epoch": 3.6,
509
+ "eval_loss": 1.2331607341766357,
510
+ "eval_runtime": 4.4647,
511
+ "eval_samples_per_second": 44.796,
512
+ "eval_steps_per_second": 5.599,
513
+ "step": 180
514
+ },
515
+ {
516
+ "epoch": 3.7,
517
+ "learning_rate": 8.402061855670103e-05,
518
+ "loss": 0.9298,
519
+ "step": 185
520
+ },
521
+ {
522
+ "epoch": 3.7,
523
+ "eval_loss": 1.2324612140655518,
524
+ "eval_runtime": 4.4692,
525
+ "eval_samples_per_second": 44.751,
526
+ "eval_steps_per_second": 5.594,
527
+ "step": 185
528
+ },
529
+ {
530
+ "epoch": 3.8,
531
+ "learning_rate": 8.350515463917527e-05,
532
+ "loss": 1.3496,
533
+ "step": 190
534
+ },
535
+ {
536
+ "epoch": 3.8,
537
+ "eval_loss": 1.2315438985824585,
538
+ "eval_runtime": 4.4629,
539
+ "eval_samples_per_second": 44.814,
540
+ "eval_steps_per_second": 5.602,
541
+ "step": 190
542
+ },
543
+ {
544
+ "epoch": 3.9,
545
+ "learning_rate": 8.298969072164949e-05,
546
+ "loss": 1.1524,
547
+ "step": 195
548
+ },
549
+ {
550
+ "epoch": 3.9,
551
+ "eval_loss": 1.2303318977355957,
552
+ "eval_runtime": 4.466,
553
+ "eval_samples_per_second": 44.783,
554
+ "eval_steps_per_second": 5.598,
555
+ "step": 195
556
+ },
557
+ {
558
+ "epoch": 4.0,
559
+ "learning_rate": 8.247422680412371e-05,
560
+ "loss": 0.9595,
561
+ "step": 200
562
+ },
563
+ {
564
+ "epoch": 4.0,
565
+ "eval_loss": 1.2294974327087402,
566
+ "eval_runtime": 4.4618,
567
+ "eval_samples_per_second": 44.825,
568
+ "eval_steps_per_second": 5.603,
569
+ "step": 200
570
+ },
571
+ {
572
+ "epoch": 4.1,
573
+ "learning_rate": 8.195876288659795e-05,
574
+ "loss": 1.4978,
575
+ "step": 205
576
+ },
577
+ {
578
+ "epoch": 4.1,
579
+ "eval_loss": 1.228881597518921,
580
+ "eval_runtime": 4.4634,
581
+ "eval_samples_per_second": 44.809,
582
+ "eval_steps_per_second": 5.601,
583
+ "step": 205
584
+ },
585
+ {
586
+ "epoch": 4.2,
587
+ "learning_rate": 8.144329896907217e-05,
588
+ "loss": 1.0768,
589
+ "step": 210
590
+ },
591
+ {
592
+ "epoch": 4.2,
593
+ "eval_loss": 1.2280452251434326,
594
+ "eval_runtime": 4.4676,
595
+ "eval_samples_per_second": 44.766,
596
+ "eval_steps_per_second": 5.596,
597
+ "step": 210
598
+ },
599
+ {
600
+ "epoch": 4.3,
601
+ "learning_rate": 8.092783505154639e-05,
602
+ "loss": 1.2207,
603
+ "step": 215
604
+ },
605
+ {
606
+ "epoch": 4.3,
607
+ "eval_loss": 1.2275255918502808,
608
+ "eval_runtime": 4.4621,
609
+ "eval_samples_per_second": 44.822,
610
+ "eval_steps_per_second": 5.603,
611
+ "step": 215
612
+ },
613
+ {
614
+ "epoch": 4.4,
615
+ "learning_rate": 8.041237113402063e-05,
616
+ "loss": 1.0792,
617
+ "step": 220
618
+ },
619
+ {
620
+ "epoch": 4.4,
621
+ "eval_loss": 1.2285792827606201,
622
+ "eval_runtime": 4.4624,
623
+ "eval_samples_per_second": 44.819,
624
+ "eval_steps_per_second": 5.602,
625
+ "step": 220
626
+ },
627
+ {
628
+ "epoch": 4.5,
629
+ "learning_rate": 7.989690721649485e-05,
630
+ "loss": 0.9888,
631
+ "step": 225
632
+ },
633
+ {
634
+ "epoch": 4.5,
635
+ "eval_loss": 1.227547287940979,
636
+ "eval_runtime": 4.4611,
637
+ "eval_samples_per_second": 44.832,
638
+ "eval_steps_per_second": 5.604,
639
+ "step": 225
640
+ },
641
+ {
642
+ "epoch": 4.6,
643
+ "learning_rate": 7.938144329896907e-05,
644
+ "loss": 1.4156,
645
+ "step": 230
646
+ },
647
+ {
648
+ "epoch": 4.6,
649
+ "eval_loss": 1.2268065214157104,
650
+ "eval_runtime": 4.4631,
651
+ "eval_samples_per_second": 44.811,
652
+ "eval_steps_per_second": 5.601,
653
+ "step": 230
654
+ },
655
+ {
656
+ "epoch": 4.7,
657
+ "learning_rate": 7.88659793814433e-05,
658
+ "loss": 0.8983,
659
+ "step": 235
660
+ },
661
+ {
662
+ "epoch": 4.7,
663
+ "eval_loss": 1.2261872291564941,
664
+ "eval_runtime": 4.4627,
665
+ "eval_samples_per_second": 44.816,
666
+ "eval_steps_per_second": 5.602,
667
+ "step": 235
668
+ },
669
+ {
670
+ "epoch": 4.8,
671
+ "learning_rate": 7.835051546391753e-05,
672
+ "loss": 1.2464,
673
+ "step": 240
674
+ },
675
+ {
676
+ "epoch": 4.8,
677
+ "eval_loss": 1.2259939908981323,
678
+ "eval_runtime": 4.4625,
679
+ "eval_samples_per_second": 44.818,
680
+ "eval_steps_per_second": 5.602,
681
+ "step": 240
682
+ },
683
+ {
684
+ "epoch": 4.9,
685
+ "learning_rate": 7.783505154639175e-05,
686
+ "loss": 1.0682,
687
+ "step": 245
688
+ },
689
+ {
690
+ "epoch": 4.9,
691
+ "eval_loss": 1.2249301671981812,
692
+ "eval_runtime": 4.4625,
693
+ "eval_samples_per_second": 44.818,
694
+ "eval_steps_per_second": 5.602,
695
+ "step": 245
696
+ },
697
+ {
698
+ "epoch": 5.0,
699
+ "learning_rate": 7.731958762886599e-05,
700
+ "loss": 0.9483,
701
+ "step": 250
702
+ },
703
+ {
704
+ "epoch": 5.0,
705
+ "eval_loss": 1.224156141281128,
706
+ "eval_runtime": 4.4608,
707
+ "eval_samples_per_second": 44.835,
708
+ "eval_steps_per_second": 5.604,
709
+ "step": 250
710
+ },
711
+ {
712
+ "epoch": 5.1,
713
+ "learning_rate": 7.680412371134021e-05,
714
+ "loss": 1.4381,
715
+ "step": 255
716
+ },
717
+ {
718
+ "epoch": 5.1,
719
+ "eval_loss": 1.2236390113830566,
720
+ "eval_runtime": 4.4621,
721
+ "eval_samples_per_second": 44.822,
722
+ "eval_steps_per_second": 5.603,
723
+ "step": 255
724
+ },
725
+ {
726
+ "epoch": 5.2,
727
+ "learning_rate": 7.628865979381443e-05,
728
+ "loss": 0.948,
729
+ "step": 260
730
+ },
731
+ {
732
+ "epoch": 5.2,
733
+ "eval_loss": 1.2235738039016724,
734
+ "eval_runtime": 4.4614,
735
+ "eval_samples_per_second": 44.829,
736
+ "eval_steps_per_second": 5.604,
737
+ "step": 260
738
+ },
739
+ {
740
+ "epoch": 5.3,
741
+ "learning_rate": 7.577319587628867e-05,
742
+ "loss": 1.2122,
743
+ "step": 265
744
+ },
745
+ {
746
+ "epoch": 5.3,
747
+ "eval_loss": 1.2235658168792725,
748
+ "eval_runtime": 4.4625,
749
+ "eval_samples_per_second": 44.818,
750
+ "eval_steps_per_second": 5.602,
751
+ "step": 265
752
+ },
753
+ {
754
+ "epoch": 5.4,
755
+ "learning_rate": 7.525773195876289e-05,
756
+ "loss": 1.1774,
757
+ "step": 270
758
+ },
759
+ {
760
+ "epoch": 5.4,
761
+ "eval_loss": 1.223145842552185,
762
+ "eval_runtime": 4.4677,
763
+ "eval_samples_per_second": 44.766,
764
+ "eval_steps_per_second": 5.596,
765
+ "step": 270
766
+ },
767
+ {
768
+ "epoch": 5.5,
769
+ "learning_rate": 7.474226804123711e-05,
770
+ "loss": 1.0283,
771
+ "step": 275
772
+ },
773
+ {
774
+ "epoch": 5.5,
775
+ "eval_loss": 1.2216259241104126,
776
+ "eval_runtime": 4.4922,
777
+ "eval_samples_per_second": 44.522,
778
+ "eval_steps_per_second": 5.565,
779
+ "step": 275
780
+ },
781
+ {
782
+ "epoch": 5.6,
783
+ "learning_rate": 7.422680412371135e-05,
784
+ "loss": 1.3049,
785
+ "step": 280
786
+ },
787
+ {
788
+ "epoch": 5.6,
789
+ "eval_loss": 1.2210520505905151,
790
+ "eval_runtime": 4.4641,
791
+ "eval_samples_per_second": 44.801,
792
+ "eval_steps_per_second": 5.6,
793
+ "step": 280
794
+ },
795
+ {
796
+ "epoch": 5.7,
797
+ "learning_rate": 7.371134020618557e-05,
798
+ "loss": 0.9682,
799
+ "step": 285
800
+ },
801
+ {
802
+ "epoch": 5.7,
803
+ "eval_loss": 1.221419095993042,
804
+ "eval_runtime": 4.4577,
805
+ "eval_samples_per_second": 44.866,
806
+ "eval_steps_per_second": 5.608,
807
+ "step": 285
808
+ },
809
+ {
810
+ "epoch": 5.8,
811
+ "learning_rate": 7.319587628865979e-05,
812
+ "loss": 1.2808,
813
+ "step": 290
814
+ },
815
+ {
816
+ "epoch": 5.8,
817
+ "eval_loss": 1.2211226224899292,
818
+ "eval_runtime": 4.475,
819
+ "eval_samples_per_second": 44.693,
820
+ "eval_steps_per_second": 5.587,
821
+ "step": 290
822
+ },
823
+ {
824
+ "epoch": 5.9,
825
+ "learning_rate": 7.268041237113403e-05,
826
+ "loss": 1.0147,
827
+ "step": 295
828
+ },
829
+ {
830
+ "epoch": 5.9,
831
+ "eval_loss": 1.2203408479690552,
832
+ "eval_runtime": 4.4586,
833
+ "eval_samples_per_second": 44.857,
834
+ "eval_steps_per_second": 5.607,
835
+ "step": 295
836
+ },
837
+ {
838
+ "epoch": 6.0,
839
+ "learning_rate": 7.216494845360825e-05,
840
+ "loss": 0.9456,
841
+ "step": 300
842
+ },
843
+ {
844
+ "epoch": 6.0,
845
+ "eval_loss": 1.220377802848816,
846
+ "eval_runtime": 4.4629,
847
+ "eval_samples_per_second": 44.814,
848
+ "eval_steps_per_second": 5.602,
849
+ "step": 300
850
+ },
851
+ {
852
+ "epoch": 6.1,
853
+ "learning_rate": 7.164948453608247e-05,
854
+ "loss": 1.4398,
855
+ "step": 305
856
+ },
857
+ {
858
+ "epoch": 6.1,
859
+ "eval_loss": 1.2200127840042114,
860
+ "eval_runtime": 4.505,
861
+ "eval_samples_per_second": 44.396,
862
+ "eval_steps_per_second": 5.549,
863
+ "step": 305
864
+ },
865
+ {
866
+ "epoch": 6.2,
867
+ "learning_rate": 7.113402061855671e-05,
868
+ "loss": 0.9325,
869
+ "step": 310
870
+ },
871
+ {
872
+ "epoch": 6.2,
873
+ "eval_loss": 1.2199076414108276,
874
+ "eval_runtime": 4.4582,
875
+ "eval_samples_per_second": 44.861,
876
+ "eval_steps_per_second": 5.608,
877
+ "step": 310
878
+ },
879
+ {
880
+ "epoch": 6.3,
881
+ "learning_rate": 7.061855670103093e-05,
882
+ "loss": 1.2216,
883
+ "step": 315
884
+ },
885
+ {
886
+ "epoch": 6.3,
887
+ "eval_loss": 1.2199695110321045,
888
+ "eval_runtime": 4.4598,
889
+ "eval_samples_per_second": 44.845,
890
+ "eval_steps_per_second": 5.606,
891
+ "step": 315
892
+ },
893
+ {
894
+ "epoch": 6.4,
895
+ "learning_rate": 7.010309278350515e-05,
896
+ "loss": 1.1325,
897
+ "step": 320
898
+ },
899
+ {
900
+ "epoch": 6.4,
901
+ "eval_loss": 1.2204923629760742,
902
+ "eval_runtime": 4.4636,
903
+ "eval_samples_per_second": 44.807,
904
+ "eval_steps_per_second": 5.601,
905
+ "step": 320
906
+ },
907
+ {
908
+ "epoch": 6.5,
909
+ "learning_rate": 6.958762886597939e-05,
910
+ "loss": 0.9404,
911
+ "step": 325
912
+ },
913
+ {
914
+ "epoch": 6.5,
915
+ "eval_loss": 1.2200615406036377,
916
+ "eval_runtime": 4.4808,
917
+ "eval_samples_per_second": 44.635,
918
+ "eval_steps_per_second": 5.579,
919
+ "step": 325
920
+ },
921
+ {
922
+ "epoch": 6.6,
923
+ "learning_rate": 6.907216494845361e-05,
924
+ "loss": 1.3678,
925
+ "step": 330
926
+ },
927
+ {
928
+ "epoch": 6.6,
929
+ "eval_loss": 1.2192314863204956,
930
+ "eval_runtime": 4.4613,
931
+ "eval_samples_per_second": 44.83,
932
+ "eval_steps_per_second": 5.604,
933
+ "step": 330
934
+ },
935
+ {
936
+ "epoch": 6.7,
937
+ "learning_rate": 6.855670103092783e-05,
938
+ "loss": 0.9207,
939
+ "step": 335
940
+ },
941
+ {
942
+ "epoch": 6.7,
943
+ "eval_loss": 1.218888759613037,
944
+ "eval_runtime": 4.462,
945
+ "eval_samples_per_second": 44.823,
946
+ "eval_steps_per_second": 5.603,
947
+ "step": 335
948
+ },
949
+ {
950
+ "epoch": 6.8,
951
+ "learning_rate": 6.804123711340207e-05,
952
+ "loss": 1.2759,
953
+ "step": 340
954
+ },
955
+ {
956
+ "epoch": 6.8,
957
+ "eval_loss": 1.2193782329559326,
958
+ "eval_runtime": 4.4681,
959
+ "eval_samples_per_second": 44.762,
960
+ "eval_steps_per_second": 5.595,
961
+ "step": 340
962
+ },
963
+ {
964
+ "epoch": 6.9,
965
+ "learning_rate": 6.752577319587629e-05,
966
+ "loss": 1.0964,
967
+ "step": 345
968
+ },
969
+ {
970
+ "epoch": 6.9,
971
+ "eval_loss": 1.2190594673156738,
972
+ "eval_runtime": 4.4642,
973
+ "eval_samples_per_second": 44.8,
974
+ "eval_steps_per_second": 5.6,
975
+ "step": 345
976
+ },
977
+ {
978
+ "epoch": 7.0,
979
+ "learning_rate": 6.701030927835051e-05,
980
+ "loss": 0.8757,
981
+ "step": 350
982
+ },
983
+ {
984
+ "epoch": 7.0,
985
+ "eval_loss": 1.2184209823608398,
986
+ "eval_runtime": 4.4666,
987
+ "eval_samples_per_second": 44.777,
988
+ "eval_steps_per_second": 5.597,
989
+ "step": 350
990
+ }
991
+ ],
992
+ "logging_steps": 5,
993
+ "max_steps": 1000,
994
+ "num_train_epochs": 20,
995
+ "save_steps": 10,
996
+ "total_flos": 1.2443768572280832e+16,
997
+ "trial_name": null,
998
+ "trial_params": null
999
+ }
lora_li_V5/checkpoint-350/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1c6559144927c60494ec69fd4b328d5b34050e0192f6d1aa6f089d59b66616b2
3
+ size 4472