cxfan commited on
Commit
4a6038a
·
verified ·
1 Parent(s): 84a634f

Upload 28 files

Browse files
.gitattributes CHANGED
@@ -33,3 +33,4 @@ 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
+ pi_list/tokenizer.json filter=lfs diff=lfs merge=lfs -text
pi_cls/config.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "MyModel"
4
+ ],
5
+ "hidden_size": 4096,
6
+ "dias_emb_dim": 64,
7
+ "dias_embed_table_path": "./data/saved_embedding/diag_embed_micron.pkl",
8
+ "dias_mlp_dim": 512,
9
+ "drug_emb_dim": 300,
10
+ "drug_embed_table_path": "./data/saved_embedding/med_embed_molebert.pkl",
11
+ "drug_mlp_dim": 1024,
12
+ "llm_emb_dim": 4096,
13
+ "llm_name": "Llama3-Aloe-8B-Alpha",
14
+ "lora_alpha": 16,
15
+ "lora_dropout": 0.05,
16
+ "lora_r": 8,
17
+ "lora_target_modules": [
18
+ "q_proj",
19
+ "v_proj"
20
+ ],
21
+ "pat_emb_dim": 512,
22
+ "pat_embed_table_path": "./data/saved_embedding/pat_embed_raremed.pkl",
23
+ "pat_mlp_dim": 1024,
24
+ "pro_emb_dim": 64,
25
+ "pro_embed_table_path": "./data/saved_embedding/pro_embed_micron.pkl",
26
+ "pro_mlp_dim": 512,
27
+ "torch_dtype": "float16",
28
+ "transformers_version": "4.45.2",
29
+ "use_dias_embed": true,
30
+ "use_drug_embed": true,
31
+ "use_pat_embed": true,
32
+ "use_pro_embed": true
33
+ }
pi_cls/generation_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "_from_model_config": true,
3
+ "transformers_version": "4.45.2"
4
+ }
pi_cls/model-00001-of-00004.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f6f2c9183dd00f295453ac4d285ec230b8cd722c482b182e69a36b0398915e81
3
+ size 4980572264
pi_cls/model-00002-of-00004.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5af55ceb6c7b245de2573aed76cda056b895471ea026aa89e527ce375c02ff57
3
+ size 4887483120
pi_cls/model-00003-of-00004.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bfbecdfa9cdd8906a6c83d2fcb64f3a1e5f9d47a806a514fb044ff4e57980c08
3
+ size 4920610568
pi_cls/model-00004-of-00004.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1e3d5ca8a8809b7172ad98d8dbb39da0783191aabc2db447c4375ec5f190f25e
3
+ size 1339611344
pi_cls/model.safetensors.index.json ADDED
@@ -0,0 +1,442 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metadata": {
3
+ "total_size": 16128217088
4
+ },
5
+ "weight_map": {
6
+ "dias_projector.0.bias": "model-00004-of-00004.safetensors",
7
+ "dias_projector.0.weight": "model-00004-of-00004.safetensors",
8
+ "dias_projector.2.bias": "model-00004-of-00004.safetensors",
9
+ "dias_projector.2.weight": "model-00004-of-00004.safetensors",
10
+ "drug_projector.0.bias": "model-00004-of-00004.safetensors",
11
+ "drug_projector.0.weight": "model-00004-of-00004.safetensors",
12
+ "drug_projector.2.bias": "model-00004-of-00004.safetensors",
13
+ "drug_projector.2.weight": "model-00004-of-00004.safetensors",
14
+ "llm.base_model.model.lm_head.weight": "model-00004-of-00004.safetensors",
15
+ "llm.base_model.model.model.embed_tokens.weight": "model-00001-of-00004.safetensors",
16
+ "llm.base_model.model.model.layers.0.input_layernorm.weight": "model-00001-of-00004.safetensors",
17
+ "llm.base_model.model.model.layers.0.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
18
+ "llm.base_model.model.model.layers.0.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
19
+ "llm.base_model.model.model.layers.0.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
20
+ "llm.base_model.model.model.layers.0.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
21
+ "llm.base_model.model.model.layers.0.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
22
+ "llm.base_model.model.model.layers.0.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
23
+ "llm.base_model.model.model.layers.0.self_attn.q_proj.base_layer.weight": "model-00001-of-00004.safetensors",
24
+ "llm.base_model.model.model.layers.0.self_attn.q_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
25
+ "llm.base_model.model.model.layers.0.self_attn.q_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
26
+ "llm.base_model.model.model.layers.0.self_attn.v_proj.base_layer.weight": "model-00001-of-00004.safetensors",
27
+ "llm.base_model.model.model.layers.0.self_attn.v_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
28
+ "llm.base_model.model.model.layers.0.self_attn.v_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
29
+ "llm.base_model.model.model.layers.1.input_layernorm.weight": "model-00001-of-00004.safetensors",
30
+ "llm.base_model.model.model.layers.1.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
31
+ "llm.base_model.model.model.layers.1.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
32
+ "llm.base_model.model.model.layers.1.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
33
+ "llm.base_model.model.model.layers.1.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
34
+ "llm.base_model.model.model.layers.1.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
35
+ "llm.base_model.model.model.layers.1.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
36
+ "llm.base_model.model.model.layers.1.self_attn.q_proj.base_layer.weight": "model-00001-of-00004.safetensors",
37
+ "llm.base_model.model.model.layers.1.self_attn.q_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
38
+ "llm.base_model.model.model.layers.1.self_attn.q_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
39
+ "llm.base_model.model.model.layers.1.self_attn.v_proj.base_layer.weight": "model-00001-of-00004.safetensors",
40
+ "llm.base_model.model.model.layers.1.self_attn.v_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
41
+ "llm.base_model.model.model.layers.1.self_attn.v_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
42
+ "llm.base_model.model.model.layers.10.input_layernorm.weight": "model-00002-of-00004.safetensors",
43
+ "llm.base_model.model.model.layers.10.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
44
+ "llm.base_model.model.model.layers.10.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
45
+ "llm.base_model.model.model.layers.10.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
46
+ "llm.base_model.model.model.layers.10.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
47
+ "llm.base_model.model.model.layers.10.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
48
+ "llm.base_model.model.model.layers.10.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
49
+ "llm.base_model.model.model.layers.10.self_attn.q_proj.base_layer.weight": "model-00002-of-00004.safetensors",
50
+ "llm.base_model.model.model.layers.10.self_attn.q_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
51
+ "llm.base_model.model.model.layers.10.self_attn.q_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
52
+ "llm.base_model.model.model.layers.10.self_attn.v_proj.base_layer.weight": "model-00002-of-00004.safetensors",
53
+ "llm.base_model.model.model.layers.10.self_attn.v_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
54
+ "llm.base_model.model.model.layers.10.self_attn.v_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
55
+ "llm.base_model.model.model.layers.11.input_layernorm.weight": "model-00002-of-00004.safetensors",
56
+ "llm.base_model.model.model.layers.11.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
57
+ "llm.base_model.model.model.layers.11.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
58
+ "llm.base_model.model.model.layers.11.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
59
+ "llm.base_model.model.model.layers.11.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
60
+ "llm.base_model.model.model.layers.11.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
61
+ "llm.base_model.model.model.layers.11.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
62
+ "llm.base_model.model.model.layers.11.self_attn.q_proj.base_layer.weight": "model-00002-of-00004.safetensors",
63
+ "llm.base_model.model.model.layers.11.self_attn.q_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
64
+ "llm.base_model.model.model.layers.11.self_attn.q_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
65
+ "llm.base_model.model.model.layers.11.self_attn.v_proj.base_layer.weight": "model-00002-of-00004.safetensors",
66
+ "llm.base_model.model.model.layers.11.self_attn.v_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
67
+ "llm.base_model.model.model.layers.11.self_attn.v_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
68
+ "llm.base_model.model.model.layers.12.input_layernorm.weight": "model-00002-of-00004.safetensors",
69
+ "llm.base_model.model.model.layers.12.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
70
+ "llm.base_model.model.model.layers.12.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
71
+ "llm.base_model.model.model.layers.12.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
72
+ "llm.base_model.model.model.layers.12.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
73
+ "llm.base_model.model.model.layers.12.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
74
+ "llm.base_model.model.model.layers.12.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
75
+ "llm.base_model.model.model.layers.12.self_attn.q_proj.base_layer.weight": "model-00002-of-00004.safetensors",
76
+ "llm.base_model.model.model.layers.12.self_attn.q_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
77
+ "llm.base_model.model.model.layers.12.self_attn.q_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
78
+ "llm.base_model.model.model.layers.12.self_attn.v_proj.base_layer.weight": "model-00002-of-00004.safetensors",
79
+ "llm.base_model.model.model.layers.12.self_attn.v_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
80
+ "llm.base_model.model.model.layers.12.self_attn.v_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
81
+ "llm.base_model.model.model.layers.13.input_layernorm.weight": "model-00002-of-00004.safetensors",
82
+ "llm.base_model.model.model.layers.13.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
83
+ "llm.base_model.model.model.layers.13.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
84
+ "llm.base_model.model.model.layers.13.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
85
+ "llm.base_model.model.model.layers.13.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
86
+ "llm.base_model.model.model.layers.13.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
87
+ "llm.base_model.model.model.layers.13.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
88
+ "llm.base_model.model.model.layers.13.self_attn.q_proj.base_layer.weight": "model-00002-of-00004.safetensors",
89
+ "llm.base_model.model.model.layers.13.self_attn.q_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
90
+ "llm.base_model.model.model.layers.13.self_attn.q_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
91
+ "llm.base_model.model.model.layers.13.self_attn.v_proj.base_layer.weight": "model-00002-of-00004.safetensors",
92
+ "llm.base_model.model.model.layers.13.self_attn.v_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
93
+ "llm.base_model.model.model.layers.13.self_attn.v_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
94
+ "llm.base_model.model.model.layers.14.input_layernorm.weight": "model-00002-of-00004.safetensors",
95
+ "llm.base_model.model.model.layers.14.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
96
+ "llm.base_model.model.model.layers.14.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
97
+ "llm.base_model.model.model.layers.14.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
98
+ "llm.base_model.model.model.layers.14.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
99
+ "llm.base_model.model.model.layers.14.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
100
+ "llm.base_model.model.model.layers.14.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
101
+ "llm.base_model.model.model.layers.14.self_attn.q_proj.base_layer.weight": "model-00002-of-00004.safetensors",
102
+ "llm.base_model.model.model.layers.14.self_attn.q_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
103
+ "llm.base_model.model.model.layers.14.self_attn.q_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
104
+ "llm.base_model.model.model.layers.14.self_attn.v_proj.base_layer.weight": "model-00002-of-00004.safetensors",
105
+ "llm.base_model.model.model.layers.14.self_attn.v_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
106
+ "llm.base_model.model.model.layers.14.self_attn.v_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
107
+ "llm.base_model.model.model.layers.15.input_layernorm.weight": "model-00002-of-00004.safetensors",
108
+ "llm.base_model.model.model.layers.15.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
109
+ "llm.base_model.model.model.layers.15.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
110
+ "llm.base_model.model.model.layers.15.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
111
+ "llm.base_model.model.model.layers.15.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
112
+ "llm.base_model.model.model.layers.15.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
113
+ "llm.base_model.model.model.layers.15.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
114
+ "llm.base_model.model.model.layers.15.self_attn.q_proj.base_layer.weight": "model-00002-of-00004.safetensors",
115
+ "llm.base_model.model.model.layers.15.self_attn.q_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
116
+ "llm.base_model.model.model.layers.15.self_attn.q_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
117
+ "llm.base_model.model.model.layers.15.self_attn.v_proj.base_layer.weight": "model-00002-of-00004.safetensors",
118
+ "llm.base_model.model.model.layers.15.self_attn.v_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
119
+ "llm.base_model.model.model.layers.15.self_attn.v_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
120
+ "llm.base_model.model.model.layers.16.input_layernorm.weight": "model-00002-of-00004.safetensors",
121
+ "llm.base_model.model.model.layers.16.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
122
+ "llm.base_model.model.model.layers.16.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
123
+ "llm.base_model.model.model.layers.16.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
124
+ "llm.base_model.model.model.layers.16.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
125
+ "llm.base_model.model.model.layers.16.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
126
+ "llm.base_model.model.model.layers.16.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
127
+ "llm.base_model.model.model.layers.16.self_attn.q_proj.base_layer.weight": "model-00002-of-00004.safetensors",
128
+ "llm.base_model.model.model.layers.16.self_attn.q_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
129
+ "llm.base_model.model.model.layers.16.self_attn.q_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
130
+ "llm.base_model.model.model.layers.16.self_attn.v_proj.base_layer.weight": "model-00002-of-00004.safetensors",
131
+ "llm.base_model.model.model.layers.16.self_attn.v_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
132
+ "llm.base_model.model.model.layers.16.self_attn.v_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
133
+ "llm.base_model.model.model.layers.17.input_layernorm.weight": "model-00002-of-00004.safetensors",
134
+ "llm.base_model.model.model.layers.17.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
135
+ "llm.base_model.model.model.layers.17.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
136
+ "llm.base_model.model.model.layers.17.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
137
+ "llm.base_model.model.model.layers.17.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
138
+ "llm.base_model.model.model.layers.17.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
139
+ "llm.base_model.model.model.layers.17.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
140
+ "llm.base_model.model.model.layers.17.self_attn.q_proj.base_layer.weight": "model-00002-of-00004.safetensors",
141
+ "llm.base_model.model.model.layers.17.self_attn.q_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
142
+ "llm.base_model.model.model.layers.17.self_attn.q_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
143
+ "llm.base_model.model.model.layers.17.self_attn.v_proj.base_layer.weight": "model-00002-of-00004.safetensors",
144
+ "llm.base_model.model.model.layers.17.self_attn.v_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
145
+ "llm.base_model.model.model.layers.17.self_attn.v_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
146
+ "llm.base_model.model.model.layers.18.input_layernorm.weight": "model-00002-of-00004.safetensors",
147
+ "llm.base_model.model.model.layers.18.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
148
+ "llm.base_model.model.model.layers.18.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
149
+ "llm.base_model.model.model.layers.18.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
150
+ "llm.base_model.model.model.layers.18.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
151
+ "llm.base_model.model.model.layers.18.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
152
+ "llm.base_model.model.model.layers.18.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
153
+ "llm.base_model.model.model.layers.18.self_attn.q_proj.base_layer.weight": "model-00002-of-00004.safetensors",
154
+ "llm.base_model.model.model.layers.18.self_attn.q_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
155
+ "llm.base_model.model.model.layers.18.self_attn.q_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
156
+ "llm.base_model.model.model.layers.18.self_attn.v_proj.base_layer.weight": "model-00002-of-00004.safetensors",
157
+ "llm.base_model.model.model.layers.18.self_attn.v_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
158
+ "llm.base_model.model.model.layers.18.self_attn.v_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
159
+ "llm.base_model.model.model.layers.19.input_layernorm.weight": "model-00002-of-00004.safetensors",
160
+ "llm.base_model.model.model.layers.19.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
161
+ "llm.base_model.model.model.layers.19.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
162
+ "llm.base_model.model.model.layers.19.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
163
+ "llm.base_model.model.model.layers.19.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
164
+ "llm.base_model.model.model.layers.19.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
165
+ "llm.base_model.model.model.layers.19.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
166
+ "llm.base_model.model.model.layers.19.self_attn.q_proj.base_layer.weight": "model-00002-of-00004.safetensors",
167
+ "llm.base_model.model.model.layers.19.self_attn.q_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
168
+ "llm.base_model.model.model.layers.19.self_attn.q_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
169
+ "llm.base_model.model.model.layers.19.self_attn.v_proj.base_layer.weight": "model-00002-of-00004.safetensors",
170
+ "llm.base_model.model.model.layers.19.self_attn.v_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
171
+ "llm.base_model.model.model.layers.19.self_attn.v_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
172
+ "llm.base_model.model.model.layers.2.input_layernorm.weight": "model-00001-of-00004.safetensors",
173
+ "llm.base_model.model.model.layers.2.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
174
+ "llm.base_model.model.model.layers.2.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
175
+ "llm.base_model.model.model.layers.2.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
176
+ "llm.base_model.model.model.layers.2.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
177
+ "llm.base_model.model.model.layers.2.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
178
+ "llm.base_model.model.model.layers.2.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
179
+ "llm.base_model.model.model.layers.2.self_attn.q_proj.base_layer.weight": "model-00001-of-00004.safetensors",
180
+ "llm.base_model.model.model.layers.2.self_attn.q_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
181
+ "llm.base_model.model.model.layers.2.self_attn.q_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
182
+ "llm.base_model.model.model.layers.2.self_attn.v_proj.base_layer.weight": "model-00001-of-00004.safetensors",
183
+ "llm.base_model.model.model.layers.2.self_attn.v_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
184
+ "llm.base_model.model.model.layers.2.self_attn.v_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
185
+ "llm.base_model.model.model.layers.20.input_layernorm.weight": "model-00003-of-00004.safetensors",
186
+ "llm.base_model.model.model.layers.20.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
187
+ "llm.base_model.model.model.layers.20.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
188
+ "llm.base_model.model.model.layers.20.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
189
+ "llm.base_model.model.model.layers.20.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
190
+ "llm.base_model.model.model.layers.20.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
191
+ "llm.base_model.model.model.layers.20.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
192
+ "llm.base_model.model.model.layers.20.self_attn.q_proj.base_layer.weight": "model-00002-of-00004.safetensors",
193
+ "llm.base_model.model.model.layers.20.self_attn.q_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
194
+ "llm.base_model.model.model.layers.20.self_attn.q_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
195
+ "llm.base_model.model.model.layers.20.self_attn.v_proj.base_layer.weight": "model-00002-of-00004.safetensors",
196
+ "llm.base_model.model.model.layers.20.self_attn.v_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
197
+ "llm.base_model.model.model.layers.20.self_attn.v_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
198
+ "llm.base_model.model.model.layers.21.input_layernorm.weight": "model-00003-of-00004.safetensors",
199
+ "llm.base_model.model.model.layers.21.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
200
+ "llm.base_model.model.model.layers.21.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
201
+ "llm.base_model.model.model.layers.21.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
202
+ "llm.base_model.model.model.layers.21.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
203
+ "llm.base_model.model.model.layers.21.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
204
+ "llm.base_model.model.model.layers.21.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
205
+ "llm.base_model.model.model.layers.21.self_attn.q_proj.base_layer.weight": "model-00003-of-00004.safetensors",
206
+ "llm.base_model.model.model.layers.21.self_attn.q_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
207
+ "llm.base_model.model.model.layers.21.self_attn.q_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
208
+ "llm.base_model.model.model.layers.21.self_attn.v_proj.base_layer.weight": "model-00003-of-00004.safetensors",
209
+ "llm.base_model.model.model.layers.21.self_attn.v_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
210
+ "llm.base_model.model.model.layers.21.self_attn.v_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
211
+ "llm.base_model.model.model.layers.22.input_layernorm.weight": "model-00003-of-00004.safetensors",
212
+ "llm.base_model.model.model.layers.22.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
213
+ "llm.base_model.model.model.layers.22.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
214
+ "llm.base_model.model.model.layers.22.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
215
+ "llm.base_model.model.model.layers.22.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
216
+ "llm.base_model.model.model.layers.22.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
217
+ "llm.base_model.model.model.layers.22.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
218
+ "llm.base_model.model.model.layers.22.self_attn.q_proj.base_layer.weight": "model-00003-of-00004.safetensors",
219
+ "llm.base_model.model.model.layers.22.self_attn.q_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
220
+ "llm.base_model.model.model.layers.22.self_attn.q_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
221
+ "llm.base_model.model.model.layers.22.self_attn.v_proj.base_layer.weight": "model-00003-of-00004.safetensors",
222
+ "llm.base_model.model.model.layers.22.self_attn.v_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
223
+ "llm.base_model.model.model.layers.22.self_attn.v_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
224
+ "llm.base_model.model.model.layers.23.input_layernorm.weight": "model-00003-of-00004.safetensors",
225
+ "llm.base_model.model.model.layers.23.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
226
+ "llm.base_model.model.model.layers.23.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
227
+ "llm.base_model.model.model.layers.23.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
228
+ "llm.base_model.model.model.layers.23.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
229
+ "llm.base_model.model.model.layers.23.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
230
+ "llm.base_model.model.model.layers.23.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
231
+ "llm.base_model.model.model.layers.23.self_attn.q_proj.base_layer.weight": "model-00003-of-00004.safetensors",
232
+ "llm.base_model.model.model.layers.23.self_attn.q_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
233
+ "llm.base_model.model.model.layers.23.self_attn.q_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
234
+ "llm.base_model.model.model.layers.23.self_attn.v_proj.base_layer.weight": "model-00003-of-00004.safetensors",
235
+ "llm.base_model.model.model.layers.23.self_attn.v_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
236
+ "llm.base_model.model.model.layers.23.self_attn.v_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
237
+ "llm.base_model.model.model.layers.24.input_layernorm.weight": "model-00003-of-00004.safetensors",
238
+ "llm.base_model.model.model.layers.24.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
239
+ "llm.base_model.model.model.layers.24.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
240
+ "llm.base_model.model.model.layers.24.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
241
+ "llm.base_model.model.model.layers.24.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
242
+ "llm.base_model.model.model.layers.24.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
243
+ "llm.base_model.model.model.layers.24.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
244
+ "llm.base_model.model.model.layers.24.self_attn.q_proj.base_layer.weight": "model-00003-of-00004.safetensors",
245
+ "llm.base_model.model.model.layers.24.self_attn.q_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
246
+ "llm.base_model.model.model.layers.24.self_attn.q_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
247
+ "llm.base_model.model.model.layers.24.self_attn.v_proj.base_layer.weight": "model-00003-of-00004.safetensors",
248
+ "llm.base_model.model.model.layers.24.self_attn.v_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
249
+ "llm.base_model.model.model.layers.24.self_attn.v_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
250
+ "llm.base_model.model.model.layers.25.input_layernorm.weight": "model-00003-of-00004.safetensors",
251
+ "llm.base_model.model.model.layers.25.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
252
+ "llm.base_model.model.model.layers.25.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
253
+ "llm.base_model.model.model.layers.25.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
254
+ "llm.base_model.model.model.layers.25.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
255
+ "llm.base_model.model.model.layers.25.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
256
+ "llm.base_model.model.model.layers.25.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
257
+ "llm.base_model.model.model.layers.25.self_attn.q_proj.base_layer.weight": "model-00003-of-00004.safetensors",
258
+ "llm.base_model.model.model.layers.25.self_attn.q_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
259
+ "llm.base_model.model.model.layers.25.self_attn.q_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
260
+ "llm.base_model.model.model.layers.25.self_attn.v_proj.base_layer.weight": "model-00003-of-00004.safetensors",
261
+ "llm.base_model.model.model.layers.25.self_attn.v_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
262
+ "llm.base_model.model.model.layers.25.self_attn.v_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
263
+ "llm.base_model.model.model.layers.26.input_layernorm.weight": "model-00003-of-00004.safetensors",
264
+ "llm.base_model.model.model.layers.26.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
265
+ "llm.base_model.model.model.layers.26.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
266
+ "llm.base_model.model.model.layers.26.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
267
+ "llm.base_model.model.model.layers.26.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
268
+ "llm.base_model.model.model.layers.26.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
269
+ "llm.base_model.model.model.layers.26.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
270
+ "llm.base_model.model.model.layers.26.self_attn.q_proj.base_layer.weight": "model-00003-of-00004.safetensors",
271
+ "llm.base_model.model.model.layers.26.self_attn.q_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
272
+ "llm.base_model.model.model.layers.26.self_attn.q_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
273
+ "llm.base_model.model.model.layers.26.self_attn.v_proj.base_layer.weight": "model-00003-of-00004.safetensors",
274
+ "llm.base_model.model.model.layers.26.self_attn.v_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
275
+ "llm.base_model.model.model.layers.26.self_attn.v_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
276
+ "llm.base_model.model.model.layers.27.input_layernorm.weight": "model-00003-of-00004.safetensors",
277
+ "llm.base_model.model.model.layers.27.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
278
+ "llm.base_model.model.model.layers.27.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
279
+ "llm.base_model.model.model.layers.27.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
280
+ "llm.base_model.model.model.layers.27.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
281
+ "llm.base_model.model.model.layers.27.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
282
+ "llm.base_model.model.model.layers.27.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
283
+ "llm.base_model.model.model.layers.27.self_attn.q_proj.base_layer.weight": "model-00003-of-00004.safetensors",
284
+ "llm.base_model.model.model.layers.27.self_attn.q_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
285
+ "llm.base_model.model.model.layers.27.self_attn.q_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
286
+ "llm.base_model.model.model.layers.27.self_attn.v_proj.base_layer.weight": "model-00003-of-00004.safetensors",
287
+ "llm.base_model.model.model.layers.27.self_attn.v_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
288
+ "llm.base_model.model.model.layers.27.self_attn.v_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
289
+ "llm.base_model.model.model.layers.28.input_layernorm.weight": "model-00003-of-00004.safetensors",
290
+ "llm.base_model.model.model.layers.28.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
291
+ "llm.base_model.model.model.layers.28.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
292
+ "llm.base_model.model.model.layers.28.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
293
+ "llm.base_model.model.model.layers.28.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
294
+ "llm.base_model.model.model.layers.28.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
295
+ "llm.base_model.model.model.layers.28.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
296
+ "llm.base_model.model.model.layers.28.self_attn.q_proj.base_layer.weight": "model-00003-of-00004.safetensors",
297
+ "llm.base_model.model.model.layers.28.self_attn.q_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
298
+ "llm.base_model.model.model.layers.28.self_attn.q_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
299
+ "llm.base_model.model.model.layers.28.self_attn.v_proj.base_layer.weight": "model-00003-of-00004.safetensors",
300
+ "llm.base_model.model.model.layers.28.self_attn.v_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
301
+ "llm.base_model.model.model.layers.28.self_attn.v_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
302
+ "llm.base_model.model.model.layers.29.input_layernorm.weight": "model-00003-of-00004.safetensors",
303
+ "llm.base_model.model.model.layers.29.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
304
+ "llm.base_model.model.model.layers.29.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
305
+ "llm.base_model.model.model.layers.29.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
306
+ "llm.base_model.model.model.layers.29.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
307
+ "llm.base_model.model.model.layers.29.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
308
+ "llm.base_model.model.model.layers.29.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
309
+ "llm.base_model.model.model.layers.29.self_attn.q_proj.base_layer.weight": "model-00003-of-00004.safetensors",
310
+ "llm.base_model.model.model.layers.29.self_attn.q_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
311
+ "llm.base_model.model.model.layers.29.self_attn.q_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
312
+ "llm.base_model.model.model.layers.29.self_attn.v_proj.base_layer.weight": "model-00003-of-00004.safetensors",
313
+ "llm.base_model.model.model.layers.29.self_attn.v_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
314
+ "llm.base_model.model.model.layers.29.self_attn.v_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
315
+ "llm.base_model.model.model.layers.3.input_layernorm.weight": "model-00001-of-00004.safetensors",
316
+ "llm.base_model.model.model.layers.3.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
317
+ "llm.base_model.model.model.layers.3.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
318
+ "llm.base_model.model.model.layers.3.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
319
+ "llm.base_model.model.model.layers.3.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
320
+ "llm.base_model.model.model.layers.3.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
321
+ "llm.base_model.model.model.layers.3.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
322
+ "llm.base_model.model.model.layers.3.self_attn.q_proj.base_layer.weight": "model-00001-of-00004.safetensors",
323
+ "llm.base_model.model.model.layers.3.self_attn.q_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
324
+ "llm.base_model.model.model.layers.3.self_attn.q_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
325
+ "llm.base_model.model.model.layers.3.self_attn.v_proj.base_layer.weight": "model-00001-of-00004.safetensors",
326
+ "llm.base_model.model.model.layers.3.self_attn.v_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
327
+ "llm.base_model.model.model.layers.3.self_attn.v_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
328
+ "llm.base_model.model.model.layers.30.input_layernorm.weight": "model-00003-of-00004.safetensors",
329
+ "llm.base_model.model.model.layers.30.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
330
+ "llm.base_model.model.model.layers.30.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
331
+ "llm.base_model.model.model.layers.30.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
332
+ "llm.base_model.model.model.layers.30.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
333
+ "llm.base_model.model.model.layers.30.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
334
+ "llm.base_model.model.model.layers.30.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
335
+ "llm.base_model.model.model.layers.30.self_attn.q_proj.base_layer.weight": "model-00003-of-00004.safetensors",
336
+ "llm.base_model.model.model.layers.30.self_attn.q_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
337
+ "llm.base_model.model.model.layers.30.self_attn.q_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
338
+ "llm.base_model.model.model.layers.30.self_attn.v_proj.base_layer.weight": "model-00003-of-00004.safetensors",
339
+ "llm.base_model.model.model.layers.30.self_attn.v_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
340
+ "llm.base_model.model.model.layers.30.self_attn.v_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
341
+ "llm.base_model.model.model.layers.31.input_layernorm.weight": "model-00004-of-00004.safetensors",
342
+ "llm.base_model.model.model.layers.31.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
343
+ "llm.base_model.model.model.layers.31.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
344
+ "llm.base_model.model.model.layers.31.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
345
+ "llm.base_model.model.model.layers.31.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
346
+ "llm.base_model.model.model.layers.31.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
347
+ "llm.base_model.model.model.layers.31.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
348
+ "llm.base_model.model.model.layers.31.self_attn.q_proj.base_layer.weight": "model-00003-of-00004.safetensors",
349
+ "llm.base_model.model.model.layers.31.self_attn.q_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
350
+ "llm.base_model.model.model.layers.31.self_attn.q_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
351
+ "llm.base_model.model.model.layers.31.self_attn.v_proj.base_layer.weight": "model-00003-of-00004.safetensors",
352
+ "llm.base_model.model.model.layers.31.self_attn.v_proj.lora_A.default.weight": "model-00003-of-00004.safetensors",
353
+ "llm.base_model.model.model.layers.31.self_attn.v_proj.lora_B.default.weight": "model-00003-of-00004.safetensors",
354
+ "llm.base_model.model.model.layers.4.input_layernorm.weight": "model-00001-of-00004.safetensors",
355
+ "llm.base_model.model.model.layers.4.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
356
+ "llm.base_model.model.model.layers.4.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
357
+ "llm.base_model.model.model.layers.4.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
358
+ "llm.base_model.model.model.layers.4.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
359
+ "llm.base_model.model.model.layers.4.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
360
+ "llm.base_model.model.model.layers.4.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
361
+ "llm.base_model.model.model.layers.4.self_attn.q_proj.base_layer.weight": "model-00001-of-00004.safetensors",
362
+ "llm.base_model.model.model.layers.4.self_attn.q_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
363
+ "llm.base_model.model.model.layers.4.self_attn.q_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
364
+ "llm.base_model.model.model.layers.4.self_attn.v_proj.base_layer.weight": "model-00001-of-00004.safetensors",
365
+ "llm.base_model.model.model.layers.4.self_attn.v_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
366
+ "llm.base_model.model.model.layers.4.self_attn.v_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
367
+ "llm.base_model.model.model.layers.5.input_layernorm.weight": "model-00001-of-00004.safetensors",
368
+ "llm.base_model.model.model.layers.5.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
369
+ "llm.base_model.model.model.layers.5.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
370
+ "llm.base_model.model.model.layers.5.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
371
+ "llm.base_model.model.model.layers.5.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
372
+ "llm.base_model.model.model.layers.5.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
373
+ "llm.base_model.model.model.layers.5.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
374
+ "llm.base_model.model.model.layers.5.self_attn.q_proj.base_layer.weight": "model-00001-of-00004.safetensors",
375
+ "llm.base_model.model.model.layers.5.self_attn.q_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
376
+ "llm.base_model.model.model.layers.5.self_attn.q_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
377
+ "llm.base_model.model.model.layers.5.self_attn.v_proj.base_layer.weight": "model-00001-of-00004.safetensors",
378
+ "llm.base_model.model.model.layers.5.self_attn.v_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
379
+ "llm.base_model.model.model.layers.5.self_attn.v_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
380
+ "llm.base_model.model.model.layers.6.input_layernorm.weight": "model-00001-of-00004.safetensors",
381
+ "llm.base_model.model.model.layers.6.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
382
+ "llm.base_model.model.model.layers.6.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
383
+ "llm.base_model.model.model.layers.6.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
384
+ "llm.base_model.model.model.layers.6.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
385
+ "llm.base_model.model.model.layers.6.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
386
+ "llm.base_model.model.model.layers.6.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
387
+ "llm.base_model.model.model.layers.6.self_attn.q_proj.base_layer.weight": "model-00001-of-00004.safetensors",
388
+ "llm.base_model.model.model.layers.6.self_attn.q_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
389
+ "llm.base_model.model.model.layers.6.self_attn.q_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
390
+ "llm.base_model.model.model.layers.6.self_attn.v_proj.base_layer.weight": "model-00001-of-00004.safetensors",
391
+ "llm.base_model.model.model.layers.6.self_attn.v_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
392
+ "llm.base_model.model.model.layers.6.self_attn.v_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
393
+ "llm.base_model.model.model.layers.7.input_layernorm.weight": "model-00001-of-00004.safetensors",
394
+ "llm.base_model.model.model.layers.7.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
395
+ "llm.base_model.model.model.layers.7.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
396
+ "llm.base_model.model.model.layers.7.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
397
+ "llm.base_model.model.model.layers.7.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
398
+ "llm.base_model.model.model.layers.7.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
399
+ "llm.base_model.model.model.layers.7.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
400
+ "llm.base_model.model.model.layers.7.self_attn.q_proj.base_layer.weight": "model-00001-of-00004.safetensors",
401
+ "llm.base_model.model.model.layers.7.self_attn.q_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
402
+ "llm.base_model.model.model.layers.7.self_attn.q_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
403
+ "llm.base_model.model.model.layers.7.self_attn.v_proj.base_layer.weight": "model-00001-of-00004.safetensors",
404
+ "llm.base_model.model.model.layers.7.self_attn.v_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
405
+ "llm.base_model.model.model.layers.7.self_attn.v_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
406
+ "llm.base_model.model.model.layers.8.input_layernorm.weight": "model-00001-of-00004.safetensors",
407
+ "llm.base_model.model.model.layers.8.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
408
+ "llm.base_model.model.model.layers.8.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
409
+ "llm.base_model.model.model.layers.8.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
410
+ "llm.base_model.model.model.layers.8.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
411
+ "llm.base_model.model.model.layers.8.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
412
+ "llm.base_model.model.model.layers.8.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
413
+ "llm.base_model.model.model.layers.8.self_attn.q_proj.base_layer.weight": "model-00001-of-00004.safetensors",
414
+ "llm.base_model.model.model.layers.8.self_attn.q_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
415
+ "llm.base_model.model.model.layers.8.self_attn.q_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
416
+ "llm.base_model.model.model.layers.8.self_attn.v_proj.base_layer.weight": "model-00001-of-00004.safetensors",
417
+ "llm.base_model.model.model.layers.8.self_attn.v_proj.lora_A.default.weight": "model-00001-of-00004.safetensors",
418
+ "llm.base_model.model.model.layers.8.self_attn.v_proj.lora_B.default.weight": "model-00001-of-00004.safetensors",
419
+ "llm.base_model.model.model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors",
420
+ "llm.base_model.model.model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
421
+ "llm.base_model.model.model.layers.9.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
422
+ "llm.base_model.model.model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
423
+ "llm.base_model.model.model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
424
+ "llm.base_model.model.model.layers.9.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
425
+ "llm.base_model.model.model.layers.9.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
426
+ "llm.base_model.model.model.layers.9.self_attn.q_proj.base_layer.weight": "model-00002-of-00004.safetensors",
427
+ "llm.base_model.model.model.layers.9.self_attn.q_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
428
+ "llm.base_model.model.model.layers.9.self_attn.q_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
429
+ "llm.base_model.model.model.layers.9.self_attn.v_proj.base_layer.weight": "model-00002-of-00004.safetensors",
430
+ "llm.base_model.model.model.layers.9.self_attn.v_proj.lora_A.default.weight": "model-00002-of-00004.safetensors",
431
+ "llm.base_model.model.model.layers.9.self_attn.v_proj.lora_B.default.weight": "model-00002-of-00004.safetensors",
432
+ "llm.base_model.model.model.norm.weight": "model-00004-of-00004.safetensors",
433
+ "pat_projector.0.bias": "model-00004-of-00004.safetensors",
434
+ "pat_projector.0.weight": "model-00004-of-00004.safetensors",
435
+ "pat_projector.2.bias": "model-00004-of-00004.safetensors",
436
+ "pat_projector.2.weight": "model-00004-of-00004.safetensors",
437
+ "pro_projector.0.bias": "model-00004-of-00004.safetensors",
438
+ "pro_projector.0.weight": "model-00004-of-00004.safetensors",
439
+ "pro_projector.2.bias": "model-00004-of-00004.safetensors",
440
+ "pro_projector.2.weight": "model-00004-of-00004.safetensors"
441
+ }
442
+ }
pi_cls/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:03cfad5aefb03ce696e07efff1c3abce8f2a69ede2b1dd0e47314a4b66dcb4d8
3
+ size 135378693
pi_cls/rng_state_0.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b059e979e3d13eccfb38e0267e9a0bfc2bcaa9fe63fac582fba703a499a51f49
3
+ size 19639
pi_cls/rng_state_1.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a08dfb6c557f1ef1912f58e6b9f555c096b93b6c1e982c062192777b88d4e8a3
3
+ size 19639
pi_cls/rng_state_2.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0f0b0f916de96a494bb97abf5f337320d3aee074f5fd21f436d61084f8d42ad2
3
+ size 19639
pi_cls/rng_state_3.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:363620e126a6b661c7d88b02912cc0c67c6554177394118b0e604529a6104c2e
3
+ size 19639
pi_cls/rng_state_4.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6b129cdb0d9171323d2b0a27065540b3ae535349689e136805872d119d33cbb8
3
+ size 19639
pi_cls/rng_state_5.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b78854dce18cf759be4588b5d3fed668f6bf069fde25f00fa99e127adaaca482
3
+ size 19639
pi_cls/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a43bf638600b0bc916fd0839113e86def3556714f4c0d4b4244410169dc0e419
3
+ size 627
pi_cls/trainer_state.json ADDED
@@ -0,0 +1,1918 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 0.4764,
3
+ "best_model_checkpoint": "./output/0222_aloe_use_embed/checkpoint-11392",
4
+ "epoch": 1.0036835966671422,
5
+ "eval_steps": 128,
6
+ "global_step": 11392,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 8.810424830294436e-05,
13
+ "grad_norm": 1.5417201519012451,
14
+ "learning_rate": 5e-05,
15
+ "loss": 0.2594,
16
+ "step": 1
17
+ },
18
+ {
19
+ "epoch": 0.011277343782776878,
20
+ "grad_norm": 0.23772290349006653,
21
+ "learning_rate": 0.00013975424859373687,
22
+ "loss": 0.1162,
23
+ "step": 128
24
+ },
25
+ {
26
+ "epoch": 0.011277343782776878,
27
+ "eval_f1": 0.4683,
28
+ "eval_jaccard": 0.32,
29
+ "eval_loss": 0.09878014773130417,
30
+ "eval_num_drugs": 12.72,
31
+ "eval_num_drugs_gt": 24.12,
32
+ "eval_precision": 0.6935,
33
+ "eval_recall": 0.3805,
34
+ "eval_runtime": 202.7898,
35
+ "eval_samples_per_second": 74.461,
36
+ "eval_steps_per_second": 1.553,
37
+ "step": 128
38
+ },
39
+ {
40
+ "epoch": 0.022554687565553757,
41
+ "grad_norm": 0.2692396640777588,
42
+ "learning_rate": 9.882117688026184e-05,
43
+ "loss": 0.1007,
44
+ "step": 256
45
+ },
46
+ {
47
+ "epoch": 0.022554687565553757,
48
+ "eval_f1": 0.5251,
49
+ "eval_jaccard": 0.3711,
50
+ "eval_loss": 0.09602733701467514,
51
+ "eval_num_drugs": 15.36,
52
+ "eval_num_drugs_gt": 24.12,
53
+ "eval_precision": 0.6844,
54
+ "eval_recall": 0.4448,
55
+ "eval_runtime": 195.8787,
56
+ "eval_samples_per_second": 77.089,
57
+ "eval_steps_per_second": 1.608,
58
+ "step": 256
59
+ },
60
+ {
61
+ "epoch": 0.033832031348330634,
62
+ "grad_norm": 0.3894853889942169,
63
+ "learning_rate": 8.068715304598785e-05,
64
+ "loss": 0.094,
65
+ "step": 384
66
+ },
67
+ {
68
+ "epoch": 0.033832031348330634,
69
+ "eval_f1": 0.4424,
70
+ "eval_jaccard": 0.298,
71
+ "eval_loss": 0.10007771104574203,
72
+ "eval_num_drugs": 10.42,
73
+ "eval_num_drugs_gt": 24.12,
74
+ "eval_precision": 0.7377,
75
+ "eval_recall": 0.3307,
76
+ "eval_runtime": 195.8037,
77
+ "eval_samples_per_second": 77.118,
78
+ "eval_steps_per_second": 1.609,
79
+ "step": 384
80
+ },
81
+ {
82
+ "epoch": 0.045109375131107514,
83
+ "grad_norm": 0.3436169922351837,
84
+ "learning_rate": 6.987712429686843e-05,
85
+ "loss": 0.0957,
86
+ "step": 512
87
+ },
88
+ {
89
+ "epoch": 0.045109375131107514,
90
+ "eval_f1": 0.5042,
91
+ "eval_jaccard": 0.3496,
92
+ "eval_loss": 0.09312926977872849,
93
+ "eval_num_drugs": 12.82,
94
+ "eval_num_drugs_gt": 24.12,
95
+ "eval_precision": 0.7312,
96
+ "eval_recall": 0.4012,
97
+ "eval_runtime": 195.8163,
98
+ "eval_samples_per_second": 77.113,
99
+ "eval_steps_per_second": 1.609,
100
+ "step": 512
101
+ },
102
+ {
103
+ "epoch": 0.05638671891388439,
104
+ "grad_norm": 0.3193528950214386,
105
+ "learning_rate": 6.25e-05,
106
+ "loss": 0.0936,
107
+ "step": 640
108
+ },
109
+ {
110
+ "epoch": 0.05638671891388439,
111
+ "eval_f1": 0.5265,
112
+ "eval_jaccard": 0.3719,
113
+ "eval_loss": 0.09239081293344498,
114
+ "eval_num_drugs": 15.05,
115
+ "eval_num_drugs_gt": 24.12,
116
+ "eval_precision": 0.6917,
117
+ "eval_recall": 0.4447,
118
+ "eval_runtime": 195.8519,
119
+ "eval_samples_per_second": 77.099,
120
+ "eval_steps_per_second": 1.608,
121
+ "step": 640
122
+ },
123
+ {
124
+ "epoch": 0.06766406269666127,
125
+ "grad_norm": 0.4577213227748871,
126
+ "learning_rate": 5.705443307345481e-05,
127
+ "loss": 0.0912,
128
+ "step": 768
129
+ },
130
+ {
131
+ "epoch": 0.06766406269666127,
132
+ "eval_f1": 0.4896,
133
+ "eval_jaccard": 0.3425,
134
+ "eval_loss": 0.09166081994771957,
135
+ "eval_num_drugs": 12.97,
136
+ "eval_num_drugs_gt": 24.12,
137
+ "eval_precision": 0.7252,
138
+ "eval_recall": 0.3887,
139
+ "eval_runtime": 195.9265,
140
+ "eval_samples_per_second": 77.07,
141
+ "eval_steps_per_second": 1.608,
142
+ "step": 768
143
+ },
144
+ {
145
+ "epoch": 0.07894140647943815,
146
+ "grad_norm": 0.2731820344924927,
147
+ "learning_rate": 5.2822140920532286e-05,
148
+ "loss": 0.0877,
149
+ "step": 896
150
+ },
151
+ {
152
+ "epoch": 0.07894140647943815,
153
+ "eval_f1": 0.5059,
154
+ "eval_jaccard": 0.3548,
155
+ "eval_loss": 0.09068360179662704,
156
+ "eval_num_drugs": 13.69,
157
+ "eval_num_drugs_gt": 24.12,
158
+ "eval_precision": 0.7167,
159
+ "eval_recall": 0.4115,
160
+ "eval_runtime": 195.7999,
161
+ "eval_samples_per_second": 77.12,
162
+ "eval_steps_per_second": 1.609,
163
+ "step": 896
164
+ },
165
+ {
166
+ "epoch": 0.09021875026221503,
167
+ "grad_norm": 0.2719137668609619,
168
+ "learning_rate": 4.941058844013092e-05,
169
+ "loss": 0.0863,
170
+ "step": 1024
171
+ },
172
+ {
173
+ "epoch": 0.09021875026221503,
174
+ "eval_f1": 0.5368,
175
+ "eval_jaccard": 0.3819,
176
+ "eval_loss": 0.08904419839382172,
177
+ "eval_num_drugs": 15.78,
178
+ "eval_num_drugs_gt": 24.12,
179
+ "eval_precision": 0.6916,
180
+ "eval_recall": 0.4575,
181
+ "eval_runtime": 195.7912,
182
+ "eval_samples_per_second": 77.123,
183
+ "eval_steps_per_second": 1.609,
184
+ "step": 1024
185
+ },
186
+ {
187
+ "epoch": 0.10149609404499191,
188
+ "grad_norm": 0.32245615124702454,
189
+ "learning_rate": 4.658474953124562e-05,
190
+ "loss": 0.0852,
191
+ "step": 1152
192
+ },
193
+ {
194
+ "epoch": 0.10149609404499191,
195
+ "eval_f1": 0.4884,
196
+ "eval_jaccard": 0.3382,
197
+ "eval_loss": 0.09045682102441788,
198
+ "eval_num_drugs": 12.3,
199
+ "eval_num_drugs_gt": 24.12,
200
+ "eval_precision": 0.7387,
201
+ "eval_recall": 0.3797,
202
+ "eval_runtime": 195.7828,
203
+ "eval_samples_per_second": 77.126,
204
+ "eval_steps_per_second": 1.609,
205
+ "step": 1152
206
+ },
207
+ {
208
+ "epoch": 0.11277343782776877,
209
+ "grad_norm": 0.45535603165626526,
210
+ "learning_rate": 4.419417382415922e-05,
211
+ "loss": 0.0879,
212
+ "step": 1280
213
+ },
214
+ {
215
+ "epoch": 0.11277343782776877,
216
+ "eval_f1": 0.5573,
217
+ "eval_jaccard": 0.4005,
218
+ "eval_loss": 0.0893692597746849,
219
+ "eval_num_drugs": 17.23,
220
+ "eval_num_drugs_gt": 24.12,
221
+ "eval_precision": 0.6755,
222
+ "eval_recall": 0.4937,
223
+ "eval_runtime": 195.6687,
224
+ "eval_samples_per_second": 77.171,
225
+ "eval_steps_per_second": 1.61,
226
+ "step": 1280
227
+ },
228
+ {
229
+ "epoch": 0.12405078161054565,
230
+ "grad_norm": 0.2283882200717926,
231
+ "learning_rate": 4.213749140395263e-05,
232
+ "loss": 0.088,
233
+ "step": 1408
234
+ },
235
+ {
236
+ "epoch": 0.12405078161054565,
237
+ "eval_f1": 0.5172,
238
+ "eval_jaccard": 0.3636,
239
+ "eval_loss": 0.08751444518566132,
240
+ "eval_num_drugs": 13.51,
241
+ "eval_num_drugs_gt": 24.12,
242
+ "eval_precision": 0.7351,
243
+ "eval_recall": 0.4155,
244
+ "eval_runtime": 195.8082,
245
+ "eval_samples_per_second": 77.116,
246
+ "eval_steps_per_second": 1.609,
247
+ "step": 1408
248
+ },
249
+ {
250
+ "epoch": 0.13532812539332253,
251
+ "grad_norm": 0.29352277517318726,
252
+ "learning_rate": 4.0343576522993926e-05,
253
+ "loss": 0.0854,
254
+ "step": 1536
255
+ },
256
+ {
257
+ "epoch": 0.13532812539332253,
258
+ "eval_f1": 0.5465,
259
+ "eval_jaccard": 0.3926,
260
+ "eval_loss": 0.08854938298463821,
261
+ "eval_num_drugs": 15.62,
262
+ "eval_num_drugs_gt": 24.12,
263
+ "eval_precision": 0.7063,
264
+ "eval_recall": 0.4631,
265
+ "eval_runtime": 195.7835,
266
+ "eval_samples_per_second": 77.126,
267
+ "eval_steps_per_second": 1.609,
268
+ "step": 1536
269
+ },
270
+ {
271
+ "epoch": 0.14660546917609943,
272
+ "grad_norm": 0.2647421360015869,
273
+ "learning_rate": 3.876085455912764e-05,
274
+ "loss": 0.0865,
275
+ "step": 1664
276
+ },
277
+ {
278
+ "epoch": 0.14660546917609943,
279
+ "eval_f1": 0.5254,
280
+ "eval_jaccard": 0.3705,
281
+ "eval_loss": 0.08727589249610901,
282
+ "eval_num_drugs": 14.2,
283
+ "eval_num_drugs_gt": 24.12,
284
+ "eval_precision": 0.7208,
285
+ "eval_recall": 0.4289,
286
+ "eval_runtime": 195.7692,
287
+ "eval_samples_per_second": 77.132,
288
+ "eval_steps_per_second": 1.609,
289
+ "step": 1664
290
+ },
291
+ {
292
+ "epoch": 0.1578828129588763,
293
+ "grad_norm": 0.38300177454948425,
294
+ "learning_rate": 3.7350894041699797e-05,
295
+ "loss": 0.0863,
296
+ "step": 1792
297
+ },
298
+ {
299
+ "epoch": 0.1578828129588763,
300
+ "eval_f1": 0.545,
301
+ "eval_jaccard": 0.3906,
302
+ "eval_loss": 0.08650780469179153,
303
+ "eval_num_drugs": 15.84,
304
+ "eval_num_drugs_gt": 24.12,
305
+ "eval_precision": 0.7013,
306
+ "eval_recall": 0.4628,
307
+ "eval_runtime": 195.6292,
308
+ "eval_samples_per_second": 77.187,
309
+ "eval_steps_per_second": 1.61,
310
+ "step": 1792
311
+ },
312
+ {
313
+ "epoch": 0.16916015674165316,
314
+ "grad_norm": 0.2728304862976074,
315
+ "learning_rate": 3.608439182435162e-05,
316
+ "loss": 0.0835,
317
+ "step": 1920
318
+ },
319
+ {
320
+ "epoch": 0.16916015674165316,
321
+ "eval_f1": 0.5221,
322
+ "eval_jaccard": 0.3695,
323
+ "eval_loss": 0.08654700964689255,
324
+ "eval_num_drugs": 13.26,
325
+ "eval_num_drugs_gt": 24.12,
326
+ "eval_precision": 0.7471,
327
+ "eval_recall": 0.4178,
328
+ "eval_runtime": 195.6648,
329
+ "eval_samples_per_second": 77.173,
330
+ "eval_steps_per_second": 1.61,
331
+ "step": 1920
332
+ },
333
+ {
334
+ "epoch": 0.18043750052443006,
335
+ "grad_norm": 0.4084767997264862,
336
+ "learning_rate": 3.493856214843422e-05,
337
+ "loss": 0.083,
338
+ "step": 2048
339
+ },
340
+ {
341
+ "epoch": 0.18043750052443006,
342
+ "eval_f1": 0.568,
343
+ "eval_jaccard": 0.4119,
344
+ "eval_loss": 0.08511340618133545,
345
+ "eval_num_drugs": 16.65,
346
+ "eval_num_drugs_gt": 24.12,
347
+ "eval_precision": 0.7107,
348
+ "eval_recall": 0.4901,
349
+ "eval_runtime": 195.8359,
350
+ "eval_samples_per_second": 77.105,
351
+ "eval_steps_per_second": 1.608,
352
+ "step": 2048
353
+ },
354
+ {
355
+ "epoch": 0.19171484430720692,
356
+ "grad_norm": 0.2854626476764679,
357
+ "learning_rate": 3.3895384034165023e-05,
358
+ "loss": 0.0825,
359
+ "step": 2176
360
+ },
361
+ {
362
+ "epoch": 0.19171484430720692,
363
+ "eval_f1": 0.5436,
364
+ "eval_jaccard": 0.3895,
365
+ "eval_loss": 0.08521977812051773,
366
+ "eval_num_drugs": 14.88,
367
+ "eval_num_drugs_gt": 24.12,
368
+ "eval_precision": 0.7283,
369
+ "eval_recall": 0.4479,
370
+ "eval_runtime": 195.8491,
371
+ "eval_samples_per_second": 77.1,
372
+ "eval_steps_per_second": 1.608,
373
+ "step": 2176
374
+ },
375
+ {
376
+ "epoch": 0.20299218808998382,
377
+ "grad_norm": 0.3946376442909241,
378
+ "learning_rate": 3.294039229342062e-05,
379
+ "loss": 0.0824,
380
+ "step": 2304
381
+ },
382
+ {
383
+ "epoch": 0.20299218808998382,
384
+ "eval_f1": 0.5565,
385
+ "eval_jaccard": 0.4015,
386
+ "eval_loss": 0.08449013531208038,
387
+ "eval_num_drugs": 15.63,
388
+ "eval_num_drugs_gt": 24.12,
389
+ "eval_precision": 0.7266,
390
+ "eval_recall": 0.4685,
391
+ "eval_runtime": 195.8046,
392
+ "eval_samples_per_second": 77.118,
393
+ "eval_steps_per_second": 1.609,
394
+ "step": 2304
395
+ },
396
+ {
397
+ "epoch": 0.21426953187276068,
398
+ "grad_norm": 0.39819344878196716,
399
+ "learning_rate": 3.206182350266107e-05,
400
+ "loss": 0.0838,
401
+ "step": 2432
402
+ },
403
+ {
404
+ "epoch": 0.21426953187276068,
405
+ "eval_f1": 0.5598,
406
+ "eval_jaccard": 0.4052,
407
+ "eval_loss": 0.08480122685432434,
408
+ "eval_num_drugs": 15.99,
409
+ "eval_num_drugs_gt": 24.12,
410
+ "eval_precision": 0.7263,
411
+ "eval_recall": 0.4759,
412
+ "eval_runtime": 195.8068,
413
+ "eval_samples_per_second": 77.117,
414
+ "eval_steps_per_second": 1.609,
415
+ "step": 2432
416
+ },
417
+ {
418
+ "epoch": 0.22554687565553755,
419
+ "grad_norm": 0.40644770860671997,
420
+ "learning_rate": 3.125e-05,
421
+ "loss": 0.0808,
422
+ "step": 2560
423
+ },
424
+ {
425
+ "epoch": 0.22554687565553755,
426
+ "eval_f1": 0.5659,
427
+ "eval_jaccard": 0.4108,
428
+ "eval_loss": 0.08397021144628525,
429
+ "eval_num_drugs": 15.96,
430
+ "eval_num_drugs_gt": 24.12,
431
+ "eval_precision": 0.719,
432
+ "eval_recall": 0.486,
433
+ "eval_runtime": 195.678,
434
+ "eval_samples_per_second": 77.168,
435
+ "eval_steps_per_second": 1.61,
436
+ "step": 2560
437
+ },
438
+ {
439
+ "epoch": 0.23682421943831444,
440
+ "grad_norm": 0.3157194256782532,
441
+ "learning_rate": 3.049687727964166e-05,
442
+ "loss": 0.0818,
443
+ "step": 2688
444
+ },
445
+ {
446
+ "epoch": 0.23682421943831444,
447
+ "eval_f1": 0.5651,
448
+ "eval_jaccard": 0.41,
449
+ "eval_loss": 0.08456852287054062,
450
+ "eval_num_drugs": 16.17,
451
+ "eval_num_drugs_gt": 24.12,
452
+ "eval_precision": 0.7168,
453
+ "eval_recall": 0.4853,
454
+ "eval_runtime": 195.5756,
455
+ "eval_samples_per_second": 77.208,
456
+ "eval_steps_per_second": 1.611,
457
+ "step": 2688
458
+ },
459
+ {
460
+ "epoch": 0.2481015632210913,
461
+ "grad_norm": 0.39622461795806885,
462
+ "learning_rate": 2.979570591392476e-05,
463
+ "loss": 0.0833,
464
+ "step": 2816
465
+ },
466
+ {
467
+ "epoch": 0.2481015632210913,
468
+ "eval_f1": 0.5621,
469
+ "eval_jaccard": 0.4064,
470
+ "eval_loss": 0.08314160257577896,
471
+ "eval_num_drugs": 15.53,
472
+ "eval_num_drugs_gt": 24.12,
473
+ "eval_precision": 0.7432,
474
+ "eval_recall": 0.4715,
475
+ "eval_runtime": 195.5562,
476
+ "eval_samples_per_second": 77.216,
477
+ "eval_steps_per_second": 1.611,
478
+ "step": 2816
479
+ },
480
+ {
481
+ "epoch": 0.2593789070038682,
482
+ "grad_norm": 0.3746698200702667,
483
+ "learning_rate": 2.9140775257509805e-05,
484
+ "loss": 0.0819,
485
+ "step": 2944
486
+ },
487
+ {
488
+ "epoch": 0.2593789070038682,
489
+ "eval_f1": 0.5496,
490
+ "eval_jaccard": 0.3959,
491
+ "eval_loss": 0.08432751148939133,
492
+ "eval_num_drugs": 15.12,
493
+ "eval_num_drugs_gt": 24.12,
494
+ "eval_precision": 0.7236,
495
+ "eval_recall": 0.4611,
496
+ "eval_runtime": 195.7114,
497
+ "eval_samples_per_second": 77.154,
498
+ "eval_steps_per_second": 1.61,
499
+ "step": 2944
500
+ },
501
+ {
502
+ "epoch": 0.27065625078664507,
503
+ "grad_norm": 0.3464062809944153,
504
+ "learning_rate": 2.8527216536727405e-05,
505
+ "loss": 0.0815,
506
+ "step": 3072
507
+ },
508
+ {
509
+ "epoch": 0.27065625078664507,
510
+ "eval_f1": 0.5655,
511
+ "eval_jaccard": 0.4104,
512
+ "eval_loss": 0.08330993354320526,
513
+ "eval_num_drugs": 16.18,
514
+ "eval_num_drugs_gt": 24.12,
515
+ "eval_precision": 0.7149,
516
+ "eval_recall": 0.4862,
517
+ "eval_runtime": 195.7753,
518
+ "eval_samples_per_second": 77.129,
519
+ "eval_steps_per_second": 1.609,
520
+ "step": 3072
521
+ },
522
+ {
523
+ "epoch": 0.28193359456942196,
524
+ "grad_norm": 0.4193006455898285,
525
+ "learning_rate": 2.7950849718747372e-05,
526
+ "loss": 0.0838,
527
+ "step": 3200
528
+ },
529
+ {
530
+ "epoch": 0.28193359456942196,
531
+ "eval_f1": 0.5968,
532
+ "eval_jaccard": 0.4411,
533
+ "eval_loss": 0.0835125669836998,
534
+ "eval_num_drugs": 18.88,
535
+ "eval_num_drugs_gt": 24.12,
536
+ "eval_precision": 0.6926,
537
+ "eval_recall": 0.5435,
538
+ "eval_runtime": 195.749,
539
+ "eval_samples_per_second": 77.14,
540
+ "eval_steps_per_second": 1.609,
541
+ "step": 3200
542
+ },
543
+ {
544
+ "epoch": 0.29321093835219886,
545
+ "grad_norm": 0.3613840639591217,
546
+ "learning_rate": 2.7408063103344662e-05,
547
+ "loss": 0.0794,
548
+ "step": 3328
549
+ },
550
+ {
551
+ "epoch": 0.29321093835219886,
552
+ "eval_f1": 0.5667,
553
+ "eval_jaccard": 0.411,
554
+ "eval_loss": 0.08442004770040512,
555
+ "eval_num_drugs": 15.87,
556
+ "eval_num_drugs_gt": 24.12,
557
+ "eval_precision": 0.7218,
558
+ "eval_recall": 0.4827,
559
+ "eval_runtime": 195.8795,
560
+ "eval_samples_per_second": 77.088,
561
+ "eval_steps_per_second": 1.608,
562
+ "step": 3328
563
+ },
564
+ {
565
+ "epoch": 0.3044882821349757,
566
+ "grad_norm": 0.4692389965057373,
567
+ "learning_rate": 2.689571768199595e-05,
568
+ "loss": 0.0836,
569
+ "step": 3456
570
+ },
571
+ {
572
+ "epoch": 0.3044882821349757,
573
+ "eval_f1": 0.5652,
574
+ "eval_jaccard": 0.4105,
575
+ "eval_loss": 0.082563117146492,
576
+ "eval_num_drugs": 16.22,
577
+ "eval_num_drugs_gt": 24.12,
578
+ "eval_precision": 0.7177,
579
+ "eval_recall": 0.4819,
580
+ "eval_runtime": 195.7858,
581
+ "eval_samples_per_second": 77.125,
582
+ "eval_steps_per_second": 1.609,
583
+ "step": 3456
584
+ },
585
+ {
586
+ "epoch": 0.3157656259177526,
587
+ "grad_norm": 0.4498782753944397,
588
+ "learning_rate": 2.6411070460266143e-05,
589
+ "loss": 0.0829,
590
+ "step": 3584
591
+ },
592
+ {
593
+ "epoch": 0.3157656259177526,
594
+ "eval_f1": 0.5562,
595
+ "eval_jaccard": 0.4007,
596
+ "eval_loss": 0.08358080685138702,
597
+ "eval_num_drugs": 15.45,
598
+ "eval_num_drugs_gt": 24.12,
599
+ "eval_precision": 0.7373,
600
+ "eval_recall": 0.4682,
601
+ "eval_runtime": 195.7125,
602
+ "eval_samples_per_second": 77.154,
603
+ "eval_steps_per_second": 1.61,
604
+ "step": 3584
605
+ },
606
+ {
607
+ "epoch": 0.3270429697005295,
608
+ "grad_norm": 0.3039364516735077,
609
+ "learning_rate": 2.595171245429374e-05,
610
+ "loss": 0.0807,
611
+ "step": 3712
612
+ },
613
+ {
614
+ "epoch": 0.3270429697005295,
615
+ "eval_f1": 0.5737,
616
+ "eval_jaccard": 0.4194,
617
+ "eval_loss": 0.08231409639120102,
618
+ "eval_num_drugs": 16.28,
619
+ "eval_num_drugs_gt": 24.12,
620
+ "eval_precision": 0.7229,
621
+ "eval_recall": 0.4939,
622
+ "eval_runtime": 195.8345,
623
+ "eval_samples_per_second": 77.106,
624
+ "eval_steps_per_second": 1.609,
625
+ "step": 3712
626
+ },
627
+ {
628
+ "epoch": 0.3383203134833063,
629
+ "grad_norm": 0.35619407892227173,
630
+ "learning_rate": 2.5515518153991443e-05,
631
+ "loss": 0.081,
632
+ "step": 3840
633
+ },
634
+ {
635
+ "epoch": 0.3383203134833063,
636
+ "eval_f1": 0.552,
637
+ "eval_jaccard": 0.3985,
638
+ "eval_loss": 0.08209805935621262,
639
+ "eval_num_drugs": 14.51,
640
+ "eval_num_drugs_gt": 24.12,
641
+ "eval_precision": 0.7461,
642
+ "eval_recall": 0.4559,
643
+ "eval_runtime": 195.7934,
644
+ "eval_samples_per_second": 77.122,
645
+ "eval_steps_per_second": 1.609,
646
+ "step": 3840
647
+ },
648
+ {
649
+ "epoch": 0.3495976572660832,
650
+ "grad_norm": 0.3351137936115265,
651
+ "learning_rate": 2.5100604028203093e-05,
652
+ "loss": 0.0812,
653
+ "step": 3968
654
+ },
655
+ {
656
+ "epoch": 0.3495976572660832,
657
+ "eval_f1": 0.5629,
658
+ "eval_jaccard": 0.4087,
659
+ "eval_loss": 0.08269884437322617,
660
+ "eval_num_drugs": 15.55,
661
+ "eval_num_drugs_gt": 24.12,
662
+ "eval_precision": 0.7386,
663
+ "eval_recall": 0.4789,
664
+ "eval_runtime": 195.8309,
665
+ "eval_samples_per_second": 77.107,
666
+ "eval_steps_per_second": 1.609,
667
+ "step": 3968
668
+ },
669
+ {
670
+ "epoch": 0.3608750010488601,
671
+ "grad_norm": 0.39990243315696716,
672
+ "learning_rate": 2.470529422006546e-05,
673
+ "loss": 0.0812,
674
+ "step": 4096
675
+ },
676
+ {
677
+ "epoch": 0.3608750010488601,
678
+ "eval_f1": 0.5841,
679
+ "eval_jaccard": 0.4288,
680
+ "eval_loss": 0.08231902867555618,
681
+ "eval_num_drugs": 17.38,
682
+ "eval_num_drugs_gt": 24.12,
683
+ "eval_precision": 0.7097,
684
+ "eval_recall": 0.5165,
685
+ "eval_runtime": 195.693,
686
+ "eval_samples_per_second": 77.162,
687
+ "eval_steps_per_second": 1.61,
688
+ "step": 4096
689
+ },
690
+ {
691
+ "epoch": 0.37215234483163695,
692
+ "grad_norm": 0.2565082013607025,
693
+ "learning_rate": 2.4328092005047595e-05,
694
+ "loss": 0.0783,
695
+ "step": 4224
696
+ },
697
+ {
698
+ "epoch": 0.37215234483163695,
699
+ "eval_f1": 0.5713,
700
+ "eval_jaccard": 0.4162,
701
+ "eval_loss": 0.08199464529752731,
702
+ "eval_num_drugs": 15.69,
703
+ "eval_num_drugs_gt": 24.12,
704
+ "eval_precision": 0.7376,
705
+ "eval_recall": 0.4837,
706
+ "eval_runtime": 195.7555,
707
+ "eval_samples_per_second": 77.137,
708
+ "eval_steps_per_second": 1.609,
709
+ "step": 4224
710
+ },
711
+ {
712
+ "epoch": 0.38342968861441384,
713
+ "grad_norm": 0.4857080280780792,
714
+ "learning_rate": 2.3967655901480325e-05,
715
+ "loss": 0.0819,
716
+ "step": 4352
717
+ },
718
+ {
719
+ "epoch": 0.38342968861441384,
720
+ "eval_f1": 0.5795,
721
+ "eval_jaccard": 0.4247,
722
+ "eval_loss": 0.08161693811416626,
723
+ "eval_num_drugs": 15.81,
724
+ "eval_num_drugs_gt": 24.12,
725
+ "eval_precision": 0.7537,
726
+ "eval_recall": 0.4909,
727
+ "eval_runtime": 195.7017,
728
+ "eval_samples_per_second": 77.158,
729
+ "eval_steps_per_second": 1.61,
730
+ "step": 4352
731
+ },
732
+ {
733
+ "epoch": 0.39470703239719074,
734
+ "grad_norm": 0.39347517490386963,
735
+ "learning_rate": 2.36227795630767e-05,
736
+ "loss": 0.0811,
737
+ "step": 4480
738
+ },
739
+ {
740
+ "epoch": 0.39470703239719074,
741
+ "eval_f1": 0.5847,
742
+ "eval_jaccard": 0.4309,
743
+ "eval_loss": 0.08170764893293381,
744
+ "eval_num_drugs": 16.48,
745
+ "eval_num_drugs_gt": 24.12,
746
+ "eval_precision": 0.735,
747
+ "eval_recall": 0.5028,
748
+ "eval_runtime": 195.7188,
749
+ "eval_samples_per_second": 77.151,
750
+ "eval_steps_per_second": 1.609,
751
+ "step": 4480
752
+ },
753
+ {
754
+ "epoch": 0.40598437617996763,
755
+ "grad_norm": 0.35565024614334106,
756
+ "learning_rate": 2.329237476562281e-05,
757
+ "loss": 0.08,
758
+ "step": 4608
759
+ },
760
+ {
761
+ "epoch": 0.40598437617996763,
762
+ "eval_f1": 0.58,
763
+ "eval_jaccard": 0.4256,
764
+ "eval_loss": 0.08203385025262833,
765
+ "eval_num_drugs": 16.35,
766
+ "eval_num_drugs_gt": 24.12,
767
+ "eval_precision": 0.742,
768
+ "eval_recall": 0.496,
769
+ "eval_runtime": 195.752,
770
+ "eval_samples_per_second": 77.138,
771
+ "eval_steps_per_second": 1.609,
772
+ "step": 4608
773
+ },
774
+ {
775
+ "epoch": 0.41726171996274447,
776
+ "grad_norm": 0.5460488200187683,
777
+ "learning_rate": 2.2975456940431496e-05,
778
+ "loss": 0.0777,
779
+ "step": 4736
780
+ },
781
+ {
782
+ "epoch": 0.41726171996274447,
783
+ "eval_f1": 0.5931,
784
+ "eval_jaccard": 0.4399,
785
+ "eval_loss": 0.08272645622491837,
786
+ "eval_num_drugs": 18.04,
787
+ "eval_num_drugs_gt": 24.12,
788
+ "eval_precision": 0.707,
789
+ "eval_recall": 0.5312,
790
+ "eval_runtime": 195.8093,
791
+ "eval_samples_per_second": 77.116,
792
+ "eval_steps_per_second": 1.609,
793
+ "step": 4736
794
+ },
795
+ {
796
+ "epoch": 0.42853906374552136,
797
+ "grad_norm": 0.4078308343887329,
798
+ "learning_rate": 2.2671132815937868e-05,
799
+ "loss": 0.08,
800
+ "step": 4864
801
+ },
802
+ {
803
+ "epoch": 0.42853906374552136,
804
+ "eval_f1": 0.5897,
805
+ "eval_jaccard": 0.4358,
806
+ "eval_loss": 0.08148450404405594,
807
+ "eval_num_drugs": 17.21,
808
+ "eval_num_drugs_gt": 24.12,
809
+ "eval_precision": 0.7187,
810
+ "eval_recall": 0.5193,
811
+ "eval_runtime": 195.7601,
812
+ "eval_samples_per_second": 77.135,
813
+ "eval_steps_per_second": 1.609,
814
+ "step": 4864
815
+ },
816
+ {
817
+ "epoch": 0.43981640752829826,
818
+ "grad_norm": 0.3553188443183899,
819
+ "learning_rate": 2.2378589813732277e-05,
820
+ "loss": 0.0796,
821
+ "step": 4992
822
+ },
823
+ {
824
+ "epoch": 0.43981640752829826,
825
+ "eval_f1": 0.5861,
826
+ "eval_jaccard": 0.4309,
827
+ "eval_loss": 0.08156691491603851,
828
+ "eval_num_drugs": 16.24,
829
+ "eval_num_drugs_gt": 24.12,
830
+ "eval_precision": 0.7484,
831
+ "eval_recall": 0.5024,
832
+ "eval_runtime": 195.8126,
833
+ "eval_samples_per_second": 77.115,
834
+ "eval_steps_per_second": 1.609,
835
+ "step": 4992
836
+ },
837
+ {
838
+ "epoch": 0.4510937513110751,
839
+ "grad_norm": 0.5286290645599365,
840
+ "learning_rate": 2.209708691207961e-05,
841
+ "loss": 0.0761,
842
+ "step": 5120
843
+ },
844
+ {
845
+ "epoch": 0.4510937513110751,
846
+ "eval_f1": 0.5758,
847
+ "eval_jaccard": 0.4222,
848
+ "eval_loss": 0.08142111450433731,
849
+ "eval_num_drugs": 15.89,
850
+ "eval_num_drugs_gt": 24.12,
851
+ "eval_precision": 0.7446,
852
+ "eval_recall": 0.4902,
853
+ "eval_runtime": 195.7899,
854
+ "eval_samples_per_second": 77.123,
855
+ "eval_steps_per_second": 1.609,
856
+ "step": 5120
857
+ },
858
+ {
859
+ "epoch": 0.462371095093852,
860
+ "grad_norm": 0.4667411148548126,
861
+ "learning_rate": 2.1825946742799322e-05,
862
+ "loss": 0.0793,
863
+ "step": 5248
864
+ },
865
+ {
866
+ "epoch": 0.462371095093852,
867
+ "eval_f1": 0.5643,
868
+ "eval_jaccard": 0.4115,
869
+ "eval_loss": 0.08155496418476105,
870
+ "eval_num_drugs": 15.04,
871
+ "eval_num_drugs_gt": 24.12,
872
+ "eval_precision": 0.7545,
873
+ "eval_recall": 0.4697,
874
+ "eval_runtime": 195.8346,
875
+ "eval_samples_per_second": 77.106,
876
+ "eval_steps_per_second": 1.608,
877
+ "step": 5248
878
+ },
879
+ {
880
+ "epoch": 0.4736484388766289,
881
+ "grad_norm": 0.4620329737663269,
882
+ "learning_rate": 2.1564548729448567e-05,
883
+ "loss": 0.0781,
884
+ "step": 5376
885
+ },
886
+ {
887
+ "epoch": 0.4736484388766289,
888
+ "eval_f1": 0.5788,
889
+ "eval_jaccard": 0.4237,
890
+ "eval_loss": 0.0817071869969368,
891
+ "eval_num_drugs": 16.09,
892
+ "eval_num_drugs_gt": 24.12,
893
+ "eval_precision": 0.7328,
894
+ "eval_recall": 0.4961,
895
+ "eval_runtime": 195.7767,
896
+ "eval_samples_per_second": 77.129,
897
+ "eval_steps_per_second": 1.609,
898
+ "step": 5376
899
+ },
900
+ {
901
+ "epoch": 0.4849257826594058,
902
+ "grad_norm": 0.49800699949264526,
903
+ "learning_rate": 2.1312323108452298e-05,
904
+ "loss": 0.0778,
905
+ "step": 5504
906
+ },
907
+ {
908
+ "epoch": 0.4849257826594058,
909
+ "eval_f1": 0.5722,
910
+ "eval_jaccard": 0.4186,
911
+ "eval_loss": 0.08115211129188538,
912
+ "eval_num_drugs": 15.22,
913
+ "eval_num_drugs_gt": 24.12,
914
+ "eval_precision": 0.7511,
915
+ "eval_recall": 0.4801,
916
+ "eval_runtime": 195.7716,
917
+ "eval_samples_per_second": 77.131,
918
+ "eval_steps_per_second": 1.609,
919
+ "step": 5504
920
+ },
921
+ {
922
+ "epoch": 0.4962031264421826,
923
+ "grad_norm": 0.30248183012008667,
924
+ "learning_rate": 2.1068745701976316e-05,
925
+ "loss": 0.079,
926
+ "step": 5632
927
+ },
928
+ {
929
+ "epoch": 0.4962031264421826,
930
+ "eval_f1": 0.5992,
931
+ "eval_jaccard": 0.4457,
932
+ "eval_loss": 0.08108273893594742,
933
+ "eval_num_drugs": 18.39,
934
+ "eval_num_drugs_gt": 24.12,
935
+ "eval_precision": 0.7071,
936
+ "eval_recall": 0.5419,
937
+ "eval_runtime": 195.7529,
938
+ "eval_samples_per_second": 77.138,
939
+ "eval_steps_per_second": 1.609,
940
+ "step": 5632
941
+ },
942
+ {
943
+ "epoch": 0.5074804702249596,
944
+ "grad_norm": 0.37452149391174316,
945
+ "learning_rate": 2.0833333333333333e-05,
946
+ "loss": 0.0794,
947
+ "step": 5760
948
+ },
949
+ {
950
+ "epoch": 0.5074804702249596,
951
+ "eval_f1": 0.5915,
952
+ "eval_jaccard": 0.4389,
953
+ "eval_loss": 0.08032320439815521,
954
+ "eval_num_drugs": 16.98,
955
+ "eval_num_drugs_gt": 24.12,
956
+ "eval_precision": 0.7322,
957
+ "eval_recall": 0.5169,
958
+ "eval_runtime": 195.7304,
959
+ "eval_samples_per_second": 77.147,
960
+ "eval_steps_per_second": 1.609,
961
+ "step": 5760
962
+ },
963
+ {
964
+ "epoch": 0.5187578140077364,
965
+ "grad_norm": 0.36206522583961487,
966
+ "learning_rate": 2.0605639793618346e-05,
967
+ "loss": 0.0764,
968
+ "step": 5888
969
+ },
970
+ {
971
+ "epoch": 0.5187578140077364,
972
+ "eval_f1": 0.5795,
973
+ "eval_jaccard": 0.426,
974
+ "eval_loss": 0.08015798032283783,
975
+ "eval_num_drugs": 16.07,
976
+ "eval_num_drugs_gt": 24.12,
977
+ "eval_precision": 0.7413,
978
+ "eval_recall": 0.4968,
979
+ "eval_runtime": 195.7838,
980
+ "eval_samples_per_second": 77.126,
981
+ "eval_steps_per_second": 1.609,
982
+ "step": 5888
983
+ },
984
+ {
985
+ "epoch": 0.5300351577905132,
986
+ "grad_norm": 0.3741084933280945,
987
+ "learning_rate": 2.0385252282920068e-05,
988
+ "loss": 0.0802,
989
+ "step": 6016
990
+ },
991
+ {
992
+ "epoch": 0.5300351577905132,
993
+ "eval_f1": 0.5757,
994
+ "eval_jaccard": 0.4234,
995
+ "eval_loss": 0.08052277565002441,
996
+ "eval_num_drugs": 16.09,
997
+ "eval_num_drugs_gt": 24.12,
998
+ "eval_precision": 0.7429,
999
+ "eval_recall": 0.489,
1000
+ "eval_runtime": 195.7474,
1001
+ "eval_samples_per_second": 77.14,
1002
+ "eval_steps_per_second": 1.609,
1003
+ "step": 6016
1004
+ },
1005
+ {
1006
+ "epoch": 0.5413125015732901,
1007
+ "grad_norm": 0.5264722108840942,
1008
+ "learning_rate": 2.0171788261496963e-05,
1009
+ "loss": 0.0771,
1010
+ "step": 6144
1011
+ },
1012
+ {
1013
+ "epoch": 0.5413125015732901,
1014
+ "eval_f1": 0.5815,
1015
+ "eval_jaccard": 0.4278,
1016
+ "eval_loss": 0.08064176887273788,
1017
+ "eval_num_drugs": 16.36,
1018
+ "eval_num_drugs_gt": 24.12,
1019
+ "eval_precision": 0.7298,
1020
+ "eval_recall": 0.5018,
1021
+ "eval_runtime": 195.6883,
1022
+ "eval_samples_per_second": 77.164,
1023
+ "eval_steps_per_second": 1.61,
1024
+ "step": 6144
1025
+ },
1026
+ {
1027
+ "epoch": 0.552589845356067,
1028
+ "grad_norm": 0.3785838782787323,
1029
+ "learning_rate": 1.9964892656248124e-05,
1030
+ "loss": 0.0772,
1031
+ "step": 6272
1032
+ },
1033
+ {
1034
+ "epoch": 0.552589845356067,
1035
+ "eval_f1": 0.6013,
1036
+ "eval_jaccard": 0.4469,
1037
+ "eval_loss": 0.08050908893346786,
1038
+ "eval_num_drugs": 17.68,
1039
+ "eval_num_drugs_gt": 24.12,
1040
+ "eval_precision": 0.7373,
1041
+ "eval_recall": 0.5306,
1042
+ "eval_runtime": 195.7035,
1043
+ "eval_samples_per_second": 77.158,
1044
+ "eval_steps_per_second": 1.61,
1045
+ "step": 6272
1046
+ },
1047
+ {
1048
+ "epoch": 0.5638671891388439,
1049
+ "grad_norm": 0.5334848761558533,
1050
+ "learning_rate": 1.976423537605237e-05,
1051
+ "loss": 0.0771,
1052
+ "step": 6400
1053
+ },
1054
+ {
1055
+ "epoch": 0.5638671891388439,
1056
+ "eval_f1": 0.6003,
1057
+ "eval_jaccard": 0.4468,
1058
+ "eval_loss": 0.0803057849407196,
1059
+ "eval_num_drugs": 17.82,
1060
+ "eval_num_drugs_gt": 24.12,
1061
+ "eval_precision": 0.7298,
1062
+ "eval_recall": 0.5334,
1063
+ "eval_runtime": 195.7554,
1064
+ "eval_samples_per_second": 77.137,
1065
+ "eval_steps_per_second": 1.609,
1066
+ "step": 6400
1067
+ },
1068
+ {
1069
+ "epoch": 0.5751445329216208,
1070
+ "grad_norm": 0.41966477036476135,
1071
+ "learning_rate": 1.9569509096410924e-05,
1072
+ "loss": 0.0802,
1073
+ "step": 6528
1074
+ },
1075
+ {
1076
+ "epoch": 0.5751445329216208,
1077
+ "eval_f1": 0.5905,
1078
+ "eval_jaccard": 0.437,
1079
+ "eval_loss": 0.07989891618490219,
1080
+ "eval_num_drugs": 17.17,
1081
+ "eval_num_drugs_gt": 24.12,
1082
+ "eval_precision": 0.7345,
1083
+ "eval_recall": 0.5173,
1084
+ "eval_runtime": 195.6488,
1085
+ "eval_samples_per_second": 77.179,
1086
+ "eval_steps_per_second": 1.61,
1087
+ "step": 6528
1088
+ },
1089
+ {
1090
+ "epoch": 0.5864218767043977,
1091
+ "grad_norm": 0.3353288471698761,
1092
+ "learning_rate": 1.938042727956382e-05,
1093
+ "loss": 0.0769,
1094
+ "step": 6656
1095
+ },
1096
+ {
1097
+ "epoch": 0.5864218767043977,
1098
+ "eval_f1": 0.5883,
1099
+ "eval_jaccard": 0.435,
1100
+ "eval_loss": 0.08099842071533203,
1101
+ "eval_num_drugs": 17.08,
1102
+ "eval_num_drugs_gt": 24.12,
1103
+ "eval_precision": 0.7275,
1104
+ "eval_recall": 0.5168,
1105
+ "eval_runtime": 195.7812,
1106
+ "eval_samples_per_second": 77.127,
1107
+ "eval_steps_per_second": 1.609,
1108
+ "step": 6656
1109
+ },
1110
+ {
1111
+ "epoch": 0.5976992204871745,
1112
+ "grad_norm": 0.3863771855831146,
1113
+ "learning_rate": 1.9196722401060975e-05,
1114
+ "loss": 0.0733,
1115
+ "step": 6784
1116
+ },
1117
+ {
1118
+ "epoch": 0.5976992204871745,
1119
+ "eval_f1": 0.5824,
1120
+ "eval_jaccard": 0.4299,
1121
+ "eval_loss": 0.0798565074801445,
1122
+ "eval_num_drugs": 17.14,
1123
+ "eval_num_drugs_gt": 24.12,
1124
+ "eval_precision": 0.7309,
1125
+ "eval_recall": 0.508,
1126
+ "eval_runtime": 195.6748,
1127
+ "eval_samples_per_second": 77.169,
1128
+ "eval_steps_per_second": 1.61,
1129
+ "step": 6784
1130
+ },
1131
+ {
1132
+ "epoch": 0.6089765642699514,
1133
+ "grad_norm": 0.4759310185909271,
1134
+ "learning_rate": 1.9018144357818264e-05,
1135
+ "loss": 0.0761,
1136
+ "step": 6912
1137
+ },
1138
+ {
1139
+ "epoch": 0.6089765642699514,
1140
+ "eval_f1": 0.5843,
1141
+ "eval_jaccard": 0.429,
1142
+ "eval_loss": 0.0810072124004364,
1143
+ "eval_num_drugs": 16.99,
1144
+ "eval_num_drugs_gt": 24.12,
1145
+ "eval_precision": 0.7282,
1146
+ "eval_recall": 0.5099,
1147
+ "eval_runtime": 195.7644,
1148
+ "eval_samples_per_second": 77.134,
1149
+ "eval_steps_per_second": 1.609,
1150
+ "step": 6912
1151
+ },
1152
+ {
1153
+ "epoch": 0.6202539080527283,
1154
+ "grad_norm": 0.38791966438293457,
1155
+ "learning_rate": 1.8844459036110228e-05,
1156
+ "loss": 0.075,
1157
+ "step": 7040
1158
+ },
1159
+ {
1160
+ "epoch": 0.6202539080527283,
1161
+ "eval_f1": 0.5871,
1162
+ "eval_jaccard": 0.432,
1163
+ "eval_loss": 0.08122321218252182,
1164
+ "eval_num_drugs": 17.21,
1165
+ "eval_num_drugs_gt": 24.12,
1166
+ "eval_precision": 0.7211,
1167
+ "eval_recall": 0.5175,
1168
+ "eval_runtime": 195.7441,
1169
+ "eval_samples_per_second": 77.142,
1170
+ "eval_steps_per_second": 1.609,
1171
+ "step": 7040
1172
+ },
1173
+ {
1174
+ "epoch": 0.6315312518355052,
1175
+ "grad_norm": 0.3954806923866272,
1176
+ "learning_rate": 1.8675447020849898e-05,
1177
+ "loss": 0.0791,
1178
+ "step": 7168
1179
+ },
1180
+ {
1181
+ "epoch": 0.6315312518355052,
1182
+ "eval_f1": 0.5851,
1183
+ "eval_jaccard": 0.43,
1184
+ "eval_loss": 0.08063361793756485,
1185
+ "eval_num_drugs": 16.62,
1186
+ "eval_num_drugs_gt": 24.12,
1187
+ "eval_precision": 0.7364,
1188
+ "eval_recall": 0.5086,
1189
+ "eval_runtime": 195.715,
1190
+ "eval_samples_per_second": 77.153,
1191
+ "eval_steps_per_second": 1.609,
1192
+ "step": 7168
1193
+ },
1194
+ {
1195
+ "epoch": 0.6428085956182821,
1196
+ "grad_norm": 0.3953387141227722,
1197
+ "learning_rate": 1.8510902429971635e-05,
1198
+ "loss": 0.0764,
1199
+ "step": 7296
1200
+ },
1201
+ {
1202
+ "epoch": 0.6428085956182821,
1203
+ "eval_f1": 0.5976,
1204
+ "eval_jaccard": 0.4439,
1205
+ "eval_loss": 0.07970798760652542,
1206
+ "eval_num_drugs": 18.1,
1207
+ "eval_num_drugs_gt": 24.12,
1208
+ "eval_precision": 0.725,
1209
+ "eval_recall": 0.5305,
1210
+ "eval_runtime": 195.7387,
1211
+ "eval_samples_per_second": 77.144,
1212
+ "eval_steps_per_second": 1.609,
1213
+ "step": 7296
1214
+ },
1215
+ {
1216
+ "epoch": 0.654085939401059,
1217
+ "grad_norm": 0.3327171802520752,
1218
+ "learning_rate": 1.8350631859834483e-05,
1219
+ "loss": 0.0766,
1220
+ "step": 7424
1221
+ },
1222
+ {
1223
+ "epoch": 0.654085939401059,
1224
+ "eval_f1": 0.5858,
1225
+ "eval_jaccard": 0.432,
1226
+ "eval_loss": 0.07969953864812851,
1227
+ "eval_num_drugs": 16.76,
1228
+ "eval_num_drugs_gt": 24.12,
1229
+ "eval_precision": 0.7351,
1230
+ "eval_recall": 0.51,
1231
+ "eval_runtime": 195.7287,
1232
+ "eval_samples_per_second": 77.148,
1233
+ "eval_steps_per_second": 1.609,
1234
+ "step": 7424
1235
+ },
1236
+ {
1237
+ "epoch": 0.6653632831838358,
1238
+ "grad_norm": 0.4677251875400543,
1239
+ "learning_rate": 1.8194453429361938e-05,
1240
+ "loss": 0.0754,
1241
+ "step": 7552
1242
+ },
1243
+ {
1244
+ "epoch": 0.6653632831838358,
1245
+ "eval_f1": 0.5712,
1246
+ "eval_jaccard": 0.4195,
1247
+ "eval_loss": 0.07947417348623276,
1248
+ "eval_num_drugs": 15.5,
1249
+ "eval_num_drugs_gt": 24.12,
1250
+ "eval_precision": 0.7558,
1251
+ "eval_recall": 0.4822,
1252
+ "eval_runtime": 195.6955,
1253
+ "eval_samples_per_second": 77.161,
1254
+ "eval_steps_per_second": 1.61,
1255
+ "step": 7552
1256
+ },
1257
+ {
1258
+ "epoch": 0.6766406269666126,
1259
+ "grad_norm": 0.37151941657066345,
1260
+ "learning_rate": 1.804219591217581e-05,
1261
+ "loss": 0.0749,
1262
+ "step": 7680
1263
+ },
1264
+ {
1265
+ "epoch": 0.6766406269666126,
1266
+ "eval_f1": 0.592,
1267
+ "eval_jaccard": 0.4391,
1268
+ "eval_loss": 0.08006121218204498,
1269
+ "eval_num_drugs": 17.16,
1270
+ "eval_num_drugs_gt": 24.12,
1271
+ "eval_precision": 0.732,
1272
+ "eval_recall": 0.5205,
1273
+ "eval_runtime": 195.7464,
1274
+ "eval_samples_per_second": 77.141,
1275
+ "eval_steps_per_second": 1.609,
1276
+ "step": 7680
1277
+ },
1278
+ {
1279
+ "epoch": 0.6879179707493895,
1280
+ "grad_norm": 0.3027561902999878,
1281
+ "learning_rate": 1.789369794730838e-05,
1282
+ "loss": 0.0776,
1283
+ "step": 7808
1284
+ },
1285
+ {
1286
+ "epoch": 0.6879179707493895,
1287
+ "eval_f1": 0.5895,
1288
+ "eval_jaccard": 0.4354,
1289
+ "eval_loss": 0.07969165593385696,
1290
+ "eval_num_drugs": 16.87,
1291
+ "eval_num_drugs_gt": 24.12,
1292
+ "eval_precision": 0.7403,
1293
+ "eval_recall": 0.5135,
1294
+ "eval_runtime": 195.7582,
1295
+ "eval_samples_per_second": 77.136,
1296
+ "eval_steps_per_second": 1.609,
1297
+ "step": 7808
1298
+ },
1299
+ {
1300
+ "epoch": 0.6991953145321664,
1301
+ "grad_norm": 0.39215460419654846,
1302
+ "learning_rate": 1.7748807320220776e-05,
1303
+ "loss": 0.0758,
1304
+ "step": 7936
1305
+ },
1306
+ {
1307
+ "epoch": 0.6991953145321664,
1308
+ "eval_f1": 0.5807,
1309
+ "eval_jaccard": 0.4275,
1310
+ "eval_loss": 0.0798029750585556,
1311
+ "eval_num_drugs": 16.66,
1312
+ "eval_num_drugs_gt": 24.12,
1313
+ "eval_precision": 0.7346,
1314
+ "eval_recall": 0.5039,
1315
+ "eval_runtime": 195.7034,
1316
+ "eval_samples_per_second": 77.158,
1317
+ "eval_steps_per_second": 1.61,
1318
+ "step": 7936
1319
+ },
1320
+ {
1321
+ "epoch": 0.7104726583149433,
1322
+ "grad_norm": 0.5017596483230591,
1323
+ "learning_rate": 1.7607380306844094e-05,
1324
+ "loss": 0.0754,
1325
+ "step": 8064
1326
+ },
1327
+ {
1328
+ "epoch": 0.7104726583149433,
1329
+ "eval_f1": 0.5691,
1330
+ "eval_jaccard": 0.4161,
1331
+ "eval_loss": 0.0809771940112114,
1332
+ "eval_num_drugs": 15.02,
1333
+ "eval_num_drugs_gt": 24.12,
1334
+ "eval_precision": 0.7626,
1335
+ "eval_recall": 0.4748,
1336
+ "eval_runtime": 195.6836,
1337
+ "eval_samples_per_second": 77.165,
1338
+ "eval_steps_per_second": 1.61,
1339
+ "step": 8064
1340
+ },
1341
+ {
1342
+ "epoch": 0.7217500020977202,
1343
+ "grad_norm": 0.4508849084377289,
1344
+ "learning_rate": 1.746928107421711e-05,
1345
+ "loss": 0.076,
1346
+ "step": 8192
1347
+ },
1348
+ {
1349
+ "epoch": 0.7217500020977202,
1350
+ "eval_f1": 0.6147,
1351
+ "eval_jaccard": 0.4622,
1352
+ "eval_loss": 0.07949170470237732,
1353
+ "eval_num_drugs": 19.8,
1354
+ "eval_num_drugs_gt": 24.12,
1355
+ "eval_precision": 0.7027,
1356
+ "eval_recall": 0.5719,
1357
+ "eval_runtime": 195.6298,
1358
+ "eval_samples_per_second": 77.187,
1359
+ "eval_steps_per_second": 1.61,
1360
+ "step": 8192
1361
+ },
1362
+ {
1363
+ "epoch": 0.7330273458804971,
1364
+ "grad_norm": 0.4924061596393585,
1365
+ "learning_rate": 1.7334381132038412e-05,
1366
+ "loss": 0.076,
1367
+ "step": 8320
1368
+ },
1369
+ {
1370
+ "epoch": 0.7330273458804971,
1371
+ "eval_f1": 0.5685,
1372
+ "eval_jaccard": 0.4151,
1373
+ "eval_loss": 0.08067003637552261,
1374
+ "eval_num_drugs": 15.11,
1375
+ "eval_num_drugs_gt": 24.12,
1376
+ "eval_precision": 0.757,
1377
+ "eval_recall": 0.4747,
1378
+ "eval_runtime": 195.6644,
1379
+ "eval_samples_per_second": 77.173,
1380
+ "eval_steps_per_second": 1.61,
1381
+ "step": 8320
1382
+ },
1383
+ {
1384
+ "epoch": 0.7443046896632739,
1385
+ "grad_norm": 0.33014485239982605,
1386
+ "learning_rate": 1.7202558830099385e-05,
1387
+ "loss": 0.0762,
1388
+ "step": 8448
1389
+ },
1390
+ {
1391
+ "epoch": 0.7443046896632739,
1392
+ "eval_f1": 0.6012,
1393
+ "eval_jaccard": 0.4481,
1394
+ "eval_loss": 0.07921886444091797,
1395
+ "eval_num_drugs": 17.79,
1396
+ "eval_num_drugs_gt": 24.12,
1397
+ "eval_precision": 0.7356,
1398
+ "eval_recall": 0.5309,
1399
+ "eval_runtime": 195.6071,
1400
+ "eval_samples_per_second": 77.196,
1401
+ "eval_steps_per_second": 1.61,
1402
+ "step": 8448
1403
+ },
1404
+ {
1405
+ "epoch": 0.7555820334460508,
1406
+ "grad_norm": 0.3135475814342499,
1407
+ "learning_rate": 1.7073698897129783e-05,
1408
+ "loss": 0.0747,
1409
+ "step": 8576
1410
+ },
1411
+ {
1412
+ "epoch": 0.7555820334460508,
1413
+ "eval_f1": 0.6014,
1414
+ "eval_jaccard": 0.4481,
1415
+ "eval_loss": 0.07929855585098267,
1416
+ "eval_num_drugs": 17.05,
1417
+ "eval_num_drugs_gt": 24.12,
1418
+ "eval_precision": 0.7456,
1419
+ "eval_recall": 0.5259,
1420
+ "eval_runtime": 195.6688,
1421
+ "eval_samples_per_second": 77.171,
1422
+ "eval_steps_per_second": 1.61,
1423
+ "step": 8576
1424
+ },
1425
+ {
1426
+ "epoch": 0.7668593772288277,
1427
+ "grad_norm": 0.39268001914024353,
1428
+ "learning_rate": 1.6947692017082512e-05,
1429
+ "loss": 0.0771,
1430
+ "step": 8704
1431
+ },
1432
+ {
1433
+ "epoch": 0.7668593772288277,
1434
+ "eval_f1": 0.5991,
1435
+ "eval_jaccard": 0.4457,
1436
+ "eval_loss": 0.07905127853155136,
1437
+ "eval_num_drugs": 16.72,
1438
+ "eval_num_drugs_gt": 24.12,
1439
+ "eval_precision": 0.7487,
1440
+ "eval_recall": 0.52,
1441
+ "eval_runtime": 195.6858,
1442
+ "eval_samples_per_second": 77.165,
1443
+ "eval_steps_per_second": 1.61,
1444
+ "step": 8704
1445
+ },
1446
+ {
1447
+ "epoch": 0.7781367210116046,
1448
+ "grad_norm": 0.36871498823165894,
1449
+ "learning_rate": 1.682443443931767e-05,
1450
+ "loss": 0.0775,
1451
+ "step": 8832
1452
+ },
1453
+ {
1454
+ "epoch": 0.7781367210116046,
1455
+ "eval_f1": 0.6053,
1456
+ "eval_jaccard": 0.4506,
1457
+ "eval_loss": 0.07942435890436172,
1458
+ "eval_num_drugs": 18.07,
1459
+ "eval_num_drugs_gt": 24.12,
1460
+ "eval_precision": 0.7266,
1461
+ "eval_recall": 0.5417,
1462
+ "eval_runtime": 195.6902,
1463
+ "eval_samples_per_second": 77.163,
1464
+ "eval_steps_per_second": 1.61,
1465
+ "step": 8832
1466
+ },
1467
+ {
1468
+ "epoch": 0.7894140647943815,
1469
+ "grad_norm": 0.32927706837654114,
1470
+ "learning_rate": 1.6703827619526526e-05,
1471
+ "loss": 0.0757,
1472
+ "step": 8960
1473
+ },
1474
+ {
1475
+ "epoch": 0.7894140647943815,
1476
+ "eval_f1": 0.6014,
1477
+ "eval_jaccard": 0.4477,
1478
+ "eval_loss": 0.07913407683372498,
1479
+ "eval_num_drugs": 17.73,
1480
+ "eval_num_drugs_gt": 24.12,
1481
+ "eval_precision": 0.7289,
1482
+ "eval_recall": 0.5319,
1483
+ "eval_runtime": 195.6382,
1484
+ "eval_samples_per_second": 77.183,
1485
+ "eval_steps_per_second": 1.61,
1486
+ "step": 8960
1487
+ },
1488
+ {
1489
+ "epoch": 0.8006914085771584,
1490
+ "grad_norm": 0.35670703649520874,
1491
+ "learning_rate": 1.65857778885711e-05,
1492
+ "loss": 0.0791,
1493
+ "step": 9088
1494
+ },
1495
+ {
1496
+ "epoch": 0.8006914085771584,
1497
+ "eval_f1": 0.6013,
1498
+ "eval_jaccard": 0.4474,
1499
+ "eval_loss": 0.07878393679857254,
1500
+ "eval_num_drugs": 16.97,
1501
+ "eval_num_drugs_gt": 24.12,
1502
+ "eval_precision": 0.7501,
1503
+ "eval_recall": 0.5219,
1504
+ "eval_runtime": 195.6368,
1505
+ "eval_samples_per_second": 77.184,
1506
+ "eval_steps_per_second": 1.61,
1507
+ "step": 9088
1508
+ },
1509
+ {
1510
+ "epoch": 0.8119687523599353,
1511
+ "grad_norm": 0.467021107673645,
1512
+ "learning_rate": 1.647019614671031e-05,
1513
+ "loss": 0.075,
1514
+ "step": 9216
1515
+ },
1516
+ {
1517
+ "epoch": 0.8119687523599353,
1518
+ "eval_f1": 0.5871,
1519
+ "eval_jaccard": 0.4341,
1520
+ "eval_loss": 0.07932396233081818,
1521
+ "eval_num_drugs": 16.34,
1522
+ "eval_num_drugs_gt": 24.12,
1523
+ "eval_precision": 0.7538,
1524
+ "eval_recall": 0.5027,
1525
+ "eval_runtime": 195.563,
1526
+ "eval_samples_per_second": 77.213,
1527
+ "eval_steps_per_second": 1.611,
1528
+ "step": 9216
1529
+ },
1530
+ {
1531
+ "epoch": 0.823246096142712,
1532
+ "grad_norm": 0.38525936007499695,
1533
+ "learning_rate": 1.6356997580944175e-05,
1534
+ "loss": 0.078,
1535
+ "step": 9344
1536
+ },
1537
+ {
1538
+ "epoch": 0.823246096142712,
1539
+ "eval_f1": 0.5945,
1540
+ "eval_jaccard": 0.4407,
1541
+ "eval_loss": 0.07891988009214401,
1542
+ "eval_num_drugs": 17.43,
1543
+ "eval_num_drugs_gt": 24.12,
1544
+ "eval_precision": 0.7321,
1545
+ "eval_recall": 0.5239,
1546
+ "eval_runtime": 195.6748,
1547
+ "eval_samples_per_second": 77.169,
1548
+ "eval_steps_per_second": 1.61,
1549
+ "step": 9344
1550
+ },
1551
+ {
1552
+ "epoch": 0.8345234399254889,
1553
+ "grad_norm": 0.3766573369503021,
1554
+ "learning_rate": 1.6246101403438635e-05,
1555
+ "loss": 0.0775,
1556
+ "step": 9472
1557
+ },
1558
+ {
1559
+ "epoch": 0.8345234399254889,
1560
+ "eval_f1": 0.5861,
1561
+ "eval_jaccard": 0.4337,
1562
+ "eval_loss": 0.07892133295536041,
1563
+ "eval_num_drugs": 16.75,
1564
+ "eval_num_drugs_gt": 24.12,
1565
+ "eval_precision": 0.7404,
1566
+ "eval_recall": 0.5067,
1567
+ "eval_runtime": 195.583,
1568
+ "eval_samples_per_second": 77.205,
1569
+ "eval_steps_per_second": 1.611,
1570
+ "step": 9472
1571
+ },
1572
+ {
1573
+ "epoch": 0.8458007837082658,
1574
+ "grad_norm": 0.4568697214126587,
1575
+ "learning_rate": 1.613743060919757e-05,
1576
+ "loss": 0.0758,
1577
+ "step": 9600
1578
+ },
1579
+ {
1580
+ "epoch": 0.8458007837082658,
1581
+ "eval_f1": 0.5978,
1582
+ "eval_jaccard": 0.4443,
1583
+ "eval_loss": 0.0791362076997757,
1584
+ "eval_num_drugs": 17.33,
1585
+ "eval_num_drugs_gt": 24.12,
1586
+ "eval_precision": 0.7394,
1587
+ "eval_recall": 0.5233,
1588
+ "eval_runtime": 195.6035,
1589
+ "eval_samples_per_second": 77.197,
1590
+ "eval_steps_per_second": 1.61,
1591
+ "step": 9600
1592
+ },
1593
+ {
1594
+ "epoch": 0.8570781274910427,
1595
+ "grad_norm": 0.47970256209373474,
1596
+ "learning_rate": 1.6030911751330536e-05,
1597
+ "loss": 0.0766,
1598
+ "step": 9728
1599
+ },
1600
+ {
1601
+ "epoch": 0.8570781274910427,
1602
+ "eval_f1": 0.5712,
1603
+ "eval_jaccard": 0.4201,
1604
+ "eval_loss": 0.07883810997009277,
1605
+ "eval_num_drugs": 15.38,
1606
+ "eval_num_drugs_gt": 24.12,
1607
+ "eval_precision": 0.7548,
1608
+ "eval_recall": 0.4783,
1609
+ "eval_runtime": 195.622,
1610
+ "eval_samples_per_second": 77.19,
1611
+ "eval_steps_per_second": 1.61,
1612
+ "step": 9728
1613
+ },
1614
+ {
1615
+ "epoch": 0.8683554712738196,
1616
+ "grad_norm": 0.4435725510120392,
1617
+ "learning_rate": 1.5926474732425798e-05,
1618
+ "loss": 0.0751,
1619
+ "step": 9856
1620
+ },
1621
+ {
1622
+ "epoch": 0.8683554712738196,
1623
+ "eval_f1": 0.5988,
1624
+ "eval_jaccard": 0.4461,
1625
+ "eval_loss": 0.07905417680740356,
1626
+ "eval_num_drugs": 17.44,
1627
+ "eval_num_drugs_gt": 24.12,
1628
+ "eval_precision": 0.7354,
1629
+ "eval_recall": 0.5294,
1630
+ "eval_runtime": 195.6283,
1631
+ "eval_samples_per_second": 77.187,
1632
+ "eval_steps_per_second": 1.61,
1633
+ "step": 9856
1634
+ },
1635
+ {
1636
+ "epoch": 0.8796328150565965,
1637
+ "grad_norm": 0.44593748450279236,
1638
+ "learning_rate": 1.582405261068229e-05,
1639
+ "loss": 0.0739,
1640
+ "step": 9984
1641
+ },
1642
+ {
1643
+ "epoch": 0.8796328150565965,
1644
+ "eval_f1": 0.5861,
1645
+ "eval_jaccard": 0.4368,
1646
+ "eval_loss": 0.07844545692205429,
1647
+ "eval_num_drugs": 16.53,
1648
+ "eval_num_drugs_gt": 24.12,
1649
+ "eval_precision": 0.7405,
1650
+ "eval_recall": 0.5069,
1651
+ "eval_runtime": 195.5497,
1652
+ "eval_samples_per_second": 77.218,
1653
+ "eval_steps_per_second": 1.611,
1654
+ "step": 9984
1655
+ },
1656
+ {
1657
+ "epoch": 0.8909101588393734,
1658
+ "grad_norm": 0.4424314796924591,
1659
+ "learning_rate": 1.572358141958211e-05,
1660
+ "loss": 0.0767,
1661
+ "step": 10112
1662
+ },
1663
+ {
1664
+ "epoch": 0.8909101588393734,
1665
+ "eval_f1": 0.5993,
1666
+ "eval_jaccard": 0.4471,
1667
+ "eval_loss": 0.07896988093852997,
1668
+ "eval_num_drugs": 17.54,
1669
+ "eval_num_drugs_gt": 24.12,
1670
+ "eval_precision": 0.7243,
1671
+ "eval_recall": 0.5324,
1672
+ "eval_runtime": 195.5885,
1673
+ "eval_samples_per_second": 77.203,
1674
+ "eval_steps_per_second": 1.611,
1675
+ "step": 10112
1676
+ },
1677
+ {
1678
+ "epoch": 0.9021875026221502,
1679
+ "grad_norm": 0.38866597414016724,
1680
+ "learning_rate": 1.5625e-05,
1681
+ "loss": 0.0763,
1682
+ "step": 10240
1683
+ },
1684
+ {
1685
+ "epoch": 0.9021875026221502,
1686
+ "eval_f1": 0.6029,
1687
+ "eval_jaccard": 0.4488,
1688
+ "eval_loss": 0.07891592383384705,
1689
+ "eval_num_drugs": 17.38,
1690
+ "eval_num_drugs_gt": 24.12,
1691
+ "eval_precision": 0.7385,
1692
+ "eval_recall": 0.5336,
1693
+ "eval_runtime": 195.5746,
1694
+ "eval_samples_per_second": 77.208,
1695
+ "eval_steps_per_second": 1.611,
1696
+ "step": 10240
1697
+ },
1698
+ {
1699
+ "epoch": 0.9134648464049271,
1700
+ "grad_norm": 0.31933003664016724,
1701
+ "learning_rate": 1.5528249843748542e-05,
1702
+ "loss": 0.0739,
1703
+ "step": 10368
1704
+ },
1705
+ {
1706
+ "epoch": 0.9134648464049271,
1707
+ "eval_f1": 0.5874,
1708
+ "eval_jaccard": 0.4346,
1709
+ "eval_loss": 0.07923928648233414,
1710
+ "eval_num_drugs": 16.42,
1711
+ "eval_num_drugs_gt": 24.12,
1712
+ "eval_precision": 0.7319,
1713
+ "eval_recall": 0.5088,
1714
+ "eval_runtime": 195.5846,
1715
+ "eval_samples_per_second": 77.204,
1716
+ "eval_steps_per_second": 1.611,
1717
+ "step": 10368
1718
+ },
1719
+ {
1720
+ "epoch": 0.924742190187704,
1721
+ "grad_norm": 0.5055702328681946,
1722
+ "learning_rate": 1.543327494764984e-05,
1723
+ "loss": 0.0763,
1724
+ "step": 10496
1725
+ },
1726
+ {
1727
+ "epoch": 0.924742190187704,
1728
+ "eval_f1": 0.6055,
1729
+ "eval_jaccard": 0.4534,
1730
+ "eval_loss": 0.07852223515510559,
1731
+ "eval_num_drugs": 17.92,
1732
+ "eval_num_drugs_gt": 24.12,
1733
+ "eval_precision": 0.7339,
1734
+ "eval_recall": 0.5405,
1735
+ "eval_runtime": 195.6205,
1736
+ "eval_samples_per_second": 77.19,
1737
+ "eval_steps_per_second": 1.61,
1738
+ "step": 10496
1739
+ },
1740
+ {
1741
+ "epoch": 0.9360195339704809,
1742
+ "grad_norm": 0.41461578011512756,
1743
+ "learning_rate": 1.5340021677306748e-05,
1744
+ "loss": 0.0772,
1745
+ "step": 10624
1746
+ },
1747
+ {
1748
+ "epoch": 0.9360195339704809,
1749
+ "eval_f1": 0.5872,
1750
+ "eval_jaccard": 0.4358,
1751
+ "eval_loss": 0.07860737293958664,
1752
+ "eval_num_drugs": 16.33,
1753
+ "eval_num_drugs_gt": 24.12,
1754
+ "eval_precision": 0.7361,
1755
+ "eval_recall": 0.5047,
1756
+ "eval_runtime": 195.5859,
1757
+ "eval_samples_per_second": 77.204,
1758
+ "eval_steps_per_second": 1.611,
1759
+ "step": 10624
1760
+ },
1761
+ {
1762
+ "epoch": 0.9472968777532578,
1763
+ "grad_norm": 0.3936142325401306,
1764
+ "learning_rate": 1.524843863982083e-05,
1765
+ "loss": 0.0751,
1766
+ "step": 10752
1767
+ },
1768
+ {
1769
+ "epoch": 0.9472968777532578,
1770
+ "eval_f1": 0.5702,
1771
+ "eval_jaccard": 0.4192,
1772
+ "eval_loss": 0.07872913777828217,
1773
+ "eval_num_drugs": 15.19,
1774
+ "eval_num_drugs_gt": 24.12,
1775
+ "eval_precision": 0.747,
1776
+ "eval_recall": 0.4772,
1777
+ "eval_runtime": 195.5586,
1778
+ "eval_samples_per_second": 77.215,
1779
+ "eval_steps_per_second": 1.611,
1780
+ "step": 10752
1781
+ },
1782
+ {
1783
+ "epoch": 0.9585742215360347,
1784
+ "grad_norm": 0.5581151843070984,
1785
+ "learning_rate": 1.515847656477081e-05,
1786
+ "loss": 0.0732,
1787
+ "step": 10880
1788
+ },
1789
+ {
1790
+ "epoch": 0.9585742215360347,
1791
+ "eval_f1": 0.6048,
1792
+ "eval_jaccard": 0.452,
1793
+ "eval_loss": 0.07890180498361588,
1794
+ "eval_num_drugs": 17.9,
1795
+ "eval_num_drugs_gt": 24.12,
1796
+ "eval_precision": 0.7269,
1797
+ "eval_recall": 0.5396,
1798
+ "eval_runtime": 195.611,
1799
+ "eval_samples_per_second": 77.194,
1800
+ "eval_steps_per_second": 1.61,
1801
+ "step": 10880
1802
+ },
1803
+ {
1804
+ "epoch": 0.9698515653188116,
1805
+ "grad_norm": 0.45057618618011475,
1806
+ "learning_rate": 1.507008819282538e-05,
1807
+ "loss": 0.0737,
1808
+ "step": 11008
1809
+ },
1810
+ {
1811
+ "epoch": 0.9698515653188116,
1812
+ "eval_f1": 0.5884,
1813
+ "eval_jaccard": 0.4361,
1814
+ "eval_loss": 0.0796256959438324,
1815
+ "eval_num_drugs": 16.49,
1816
+ "eval_num_drugs_gt": 24.12,
1817
+ "eval_precision": 0.7428,
1818
+ "eval_recall": 0.5092,
1819
+ "eval_runtime": 195.6093,
1820
+ "eval_samples_per_second": 77.195,
1821
+ "eval_steps_per_second": 1.61,
1822
+ "step": 11008
1823
+ },
1824
+ {
1825
+ "epoch": 0.9811289091015883,
1826
+ "grad_norm": 0.41492125391960144,
1827
+ "learning_rate": 1.4983228171418256e-05,
1828
+ "loss": 0.0746,
1829
+ "step": 11136
1830
+ },
1831
+ {
1832
+ "epoch": 0.9811289091015883,
1833
+ "eval_f1": 0.5962,
1834
+ "eval_jaccard": 0.4437,
1835
+ "eval_loss": 0.07860623300075531,
1836
+ "eval_num_drugs": 17.6,
1837
+ "eval_num_drugs_gt": 24.12,
1838
+ "eval_precision": 0.7246,
1839
+ "eval_recall": 0.5282,
1840
+ "eval_runtime": 195.559,
1841
+ "eval_samples_per_second": 77.215,
1842
+ "eval_steps_per_second": 1.611,
1843
+ "step": 11136
1844
+ },
1845
+ {
1846
+ "epoch": 0.9924062528843652,
1847
+ "grad_norm": 0.4617977440357208,
1848
+ "learning_rate": 1.489785295696238e-05,
1849
+ "loss": 0.0766,
1850
+ "step": 11264
1851
+ },
1852
+ {
1853
+ "epoch": 0.9924062528843652,
1854
+ "eval_f1": 0.622,
1855
+ "eval_jaccard": 0.4689,
1856
+ "eval_loss": 0.0785478949546814,
1857
+ "eval_num_drugs": 18.99,
1858
+ "eval_num_drugs_gt": 24.12,
1859
+ "eval_precision": 0.7236,
1860
+ "eval_recall": 0.5703,
1861
+ "eval_runtime": 195.5595,
1862
+ "eval_samples_per_second": 77.214,
1863
+ "eval_steps_per_second": 1.611,
1864
+ "step": 11264
1865
+ },
1866
+ {
1867
+ "epoch": 1.0036835966671422,
1868
+ "grad_norm": 0.395907998085022,
1869
+ "learning_rate": 1.4813920723124289e-05,
1870
+ "loss": 0.0742,
1871
+ "step": 11392
1872
+ },
1873
+ {
1874
+ "epoch": 1.0036835966671422,
1875
+ "eval_f1": 0.6299,
1876
+ "eval_jaccard": 0.4764,
1877
+ "eval_loss": 0.07868505269289017,
1878
+ "eval_num_drugs": 20.14,
1879
+ "eval_num_drugs_gt": 24.12,
1880
+ "eval_precision": 0.711,
1881
+ "eval_recall": 0.5893,
1882
+ "eval_runtime": 195.5113,
1883
+ "eval_samples_per_second": 77.233,
1884
+ "eval_steps_per_second": 1.611,
1885
+ "step": 11392
1886
+ }
1887
+ ],
1888
+ "logging_steps": 128,
1889
+ "max_steps": 227000,
1890
+ "num_input_tokens_seen": 0,
1891
+ "num_train_epochs": 20,
1892
+ "save_steps": 128,
1893
+ "stateful_callbacks": {
1894
+ "MyEarlyStoppingCallback": {
1895
+ "args": {
1896
+ "early_stopping_patience": 25,
1897
+ "early_stopping_threshold": 0.0
1898
+ },
1899
+ "attributes": {
1900
+ "early_stopping_patience_counter": 0
1901
+ }
1902
+ },
1903
+ "TrainerControl": {
1904
+ "args": {
1905
+ "should_epoch_stop": false,
1906
+ "should_evaluate": false,
1907
+ "should_log": false,
1908
+ "should_save": true,
1909
+ "should_training_stop": false
1910
+ },
1911
+ "attributes": {}
1912
+ }
1913
+ },
1914
+ "total_flos": 4.1789895853022904e+19,
1915
+ "train_batch_size": 1,
1916
+ "trial_name": null,
1917
+ "trial_params": null
1918
+ }
pi_cls/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1468745b4bc3bf5209701c04eeed508615562f58d3ba966dae36ad0a56f142a3
3
+ size 4795
pi_list/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: ./Models/sft_rethink
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 0.15.1
pi_list/adapter_config.json ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "./Models/sft_rethink",
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": 32,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "r": 32,
24
+ "rank_pattern": {},
25
+ "revision": null,
26
+ "target_modules": [
27
+ "k_proj",
28
+ "o_proj",
29
+ "gate_proj",
30
+ "down_proj",
31
+ "up_proj",
32
+ "q_proj",
33
+ "v_proj"
34
+ ],
35
+ "task_type": "CAUSAL_LM",
36
+ "trainable_token_indices": null,
37
+ "use_dora": false,
38
+ "use_rslora": false
39
+ }
pi_list/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6313c8f0c6669688e04e26ad341dfffc65060a3306a461447c30d4d21b4f3f2e
3
+ size 335604696
pi_list/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5b76883cc8d4447ff73bf0dfae9feccf4bf4a32dae216822d08d3e03a8339cef
3
+ size 671466706
pi_list/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ef95a06678320fc110d5013e7fc733c2b62a425298dcd4e860d113fd7105ed14
3
+ size 14244
pi_list/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3309cbdbec746f1916fd30e66a9c619384dd502c8a6a4e9b9e6aeb5cc725fe15
3
+ size 1064
pi_list/special_tokens_map.json ADDED
The diff for this file is too large to render. See raw diff
 
pi_list/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b21bc6853b9795dfe54a2e8bf066103b04653958599d3b9f8d3b0d0922604d39
3
+ size 20613671
pi_list/tokenizer_config.json ADDED
The diff for this file is too large to render. See raw diff
 
pi_list/trainer_state.json ADDED
The diff for this file is too large to render. See raw diff
 
pi_list/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:17efbaab563c2ae438281f901c8076f1dc455cbc1aa28dadbbdad34dbcb91a8a
3
+ size 5816