Farouk commited on
Commit
a2b2c1b
·
1 Parent(s): 307b97b

Training in progress, step 200

Browse files
adapter_config.json CHANGED
@@ -14,13 +14,13 @@
14
  "r": 64,
15
  "revision": null,
16
  "target_modules": [
17
- "v_proj",
18
- "down_proj",
19
- "gate_proj",
20
  "up_proj",
 
21
  "k_proj",
22
- "o_proj",
23
- "q_proj"
 
 
24
  ],
25
  "task_type": "CAUSAL_LM"
26
  }
 
14
  "r": 64,
15
  "revision": null,
16
  "target_modules": [
 
 
 
17
  "up_proj",
18
+ "q_proj",
19
  "k_proj",
20
+ "down_proj",
21
+ "gate_proj",
22
+ "v_proj",
23
+ "o_proj"
24
  ],
25
  "task_type": "CAUSAL_LM"
26
  }
adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:71906cb7cd37c700161633e12f19362e227d9357485fedea7fef715889cb6657
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9b304c75d2fe950dd03ec74af4fdec1e8843d6732e5fe7bf3700ba7e03fcf3be
3
  size 319977229
checkpoint-200/README.md CHANGED
@@ -4,6 +4,17 @@ library_name: peft
4
  ## Training procedure
5
 
6
 
 
 
 
 
 
 
 
 
 
 
 
7
  The following `bitsandbytes` quantization config was used during training:
8
  - load_in_8bit: False
9
  - load_in_4bit: True
@@ -16,5 +27,6 @@ The following `bitsandbytes` quantization config was used during training:
16
  - bnb_4bit_compute_dtype: bfloat16
17
  ### Framework versions
18
 
 
19
 
20
  - PEFT 0.4.0
 
4
  ## Training procedure
5
 
6
 
7
+ The following `bitsandbytes` quantization config was used during training:
8
+ - load_in_8bit: False
9
+ - load_in_4bit: True
10
+ - llm_int8_threshold: 6.0
11
+ - llm_int8_skip_modules: None
12
+ - llm_int8_enable_fp32_cpu_offload: False
13
+ - llm_int8_has_fp16_weight: False
14
+ - bnb_4bit_quant_type: nf4
15
+ - bnb_4bit_use_double_quant: True
16
+ - bnb_4bit_compute_dtype: bfloat16
17
+
18
  The following `bitsandbytes` quantization config was used during training:
19
  - load_in_8bit: False
20
  - load_in_4bit: True
 
27
  - bnb_4bit_compute_dtype: bfloat16
28
  ### Framework versions
29
 
30
+ - PEFT 0.4.0
31
 
32
  - PEFT 0.4.0
checkpoint-200/adapter_config.json CHANGED
@@ -14,13 +14,13 @@
14
  "r": 64,
15
  "revision": null,
16
  "target_modules": [
17
- "v_proj",
18
- "down_proj",
19
- "gate_proj",
20
  "up_proj",
 
21
  "k_proj",
22
- "o_proj",
23
- "q_proj"
 
 
24
  ],
25
  "task_type": "CAUSAL_LM"
26
  }
 
14
  "r": 64,
15
  "revision": null,
16
  "target_modules": [
 
 
 
17
  "up_proj",
18
+ "q_proj",
19
  "k_proj",
20
+ "down_proj",
21
+ "gate_proj",
22
+ "v_proj",
23
+ "o_proj"
24
  ],
25
  "task_type": "CAUSAL_LM"
26
  }
checkpoint-200/adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:02f5290587d3eefd596838b4bfefb444cae13257dedb81baa7bdd283eb97d590
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9b304c75d2fe950dd03ec74af4fdec1e8843d6732e5fe7bf3700ba7e03fcf3be
3
  size 319977229
checkpoint-200/optimizer.pt CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d29f27fb930230ffd6ea6f0a1639297c854e9531ee60eacd2b8b4c0ef4047dbd
3
  size 1279539525
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:615c84ce32cd736413f4264f6ca7835a688c96be8de0e506a24dd2ade9ea58aa
3
  size 1279539525
checkpoint-200/rng_state.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:5f82cc9eb0b5433c918393971f9b0774b51dae507d7a4f06a2e26ae2620a7d09
3
  size 14511
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:10f4993ff2506f03c0bd800f239dd4aaf62ed8cad781e7d41a9f1cbb4fb66002
3
  size 14511
checkpoint-200/trainer_state.json CHANGED
@@ -1,5 +1,5 @@
1
  {
2
- "best_metric": 0.8420786261558533,
3
  "best_model_checkpoint": "experts/expert-22/checkpoint-200",
4
  "epoch": 0.0769897026272736,
5
  "global_step": 200,
@@ -10,13 +10,13 @@
10
  {
11
  "epoch": 0.0,
12
  "learning_rate": 0.0002,
13
- "loss": 0.9402,
14
  "step": 10
15
  },
16
  {
17
  "epoch": 0.01,
18
  "learning_rate": 0.0002,
19
- "loss": 0.9159,
20
  "step": 20
21
  },
22
  {
@@ -28,25 +28,25 @@
28
  {
29
  "epoch": 0.02,
30
  "learning_rate": 0.0002,
31
- "loss": 0.8795,
32
  "step": 40
33
  },
34
  {
35
  "epoch": 0.02,
36
  "learning_rate": 0.0002,
37
- "loss": 0.9281,
38
  "step": 50
39
  },
40
  {
41
  "epoch": 0.02,
42
  "learning_rate": 0.0002,
43
- "loss": 0.8639,
44
  "step": 60
45
  },
46
  {
47
  "epoch": 0.03,
48
  "learning_rate": 0.0002,
49
- "loss": 0.9537,
50
  "step": 70
51
  },
52
  {
@@ -64,138 +64,138 @@
64
  {
65
  "epoch": 0.04,
66
  "learning_rate": 0.0002,
67
- "loss": 0.8651,
68
  "step": 100
69
  },
70
  {
71
  "epoch": 0.04,
72
  "learning_rate": 0.0002,
73
- "loss": 0.9332,
74
  "step": 110
75
  },
76
  {
77
  "epoch": 0.05,
78
  "learning_rate": 0.0002,
79
- "loss": 0.8883,
80
  "step": 120
81
  },
82
  {
83
  "epoch": 0.05,
84
  "learning_rate": 0.0002,
85
- "loss": 0.8945,
86
  "step": 130
87
  },
88
  {
89
  "epoch": 0.05,
90
  "learning_rate": 0.0002,
91
- "loss": 0.8675,
92
  "step": 140
93
  },
94
  {
95
  "epoch": 0.06,
96
  "learning_rate": 0.0002,
97
- "loss": 0.8583,
98
  "step": 150
99
  },
100
  {
101
  "epoch": 0.06,
102
  "learning_rate": 0.0002,
103
- "loss": 0.8992,
104
  "step": 160
105
  },
106
  {
107
  "epoch": 0.07,
108
  "learning_rate": 0.0002,
109
- "loss": 0.8667,
110
  "step": 170
111
  },
112
  {
113
  "epoch": 0.07,
114
  "learning_rate": 0.0002,
115
- "loss": 0.8367,
116
  "step": 180
117
  },
118
  {
119
  "epoch": 0.07,
120
  "learning_rate": 0.0002,
121
- "loss": 0.8495,
122
  "step": 190
123
  },
124
  {
125
  "epoch": 0.08,
126
  "learning_rate": 0.0002,
127
- "loss": 0.8338,
128
  "step": 200
129
  },
130
  {
131
  "epoch": 0.08,
132
- "eval_loss": 0.8420786261558533,
133
- "eval_runtime": 104.6029,
134
- "eval_samples_per_second": 9.56,
135
- "eval_steps_per_second": 4.78,
136
  "step": 200
137
  },
138
  {
139
  "epoch": 0.08,
140
- "mmlu_eval_accuracy": 0.49890909250031423,
141
  "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
142
  "mmlu_eval_accuracy_anatomy": 0.7142857142857143,
143
  "mmlu_eval_accuracy_astronomy": 0.4375,
144
  "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
145
- "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
146
- "mmlu_eval_accuracy_college_biology": 0.4375,
147
  "mmlu_eval_accuracy_college_chemistry": 0.25,
148
  "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
149
  "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
150
  "mmlu_eval_accuracy_college_medicine": 0.36363636363636365,
151
  "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
152
  "mmlu_eval_accuracy_computer_security": 0.6363636363636364,
153
- "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
154
  "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
155
- "mmlu_eval_accuracy_electrical_engineering": 0.25,
156
- "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
157
  "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
158
  "mmlu_eval_accuracy_global_facts": 0.6,
159
- "mmlu_eval_accuracy_high_school_biology": 0.5,
160
  "mmlu_eval_accuracy_high_school_chemistry": 0.2727272727272727,
161
  "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
162
- "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
163
  "mmlu_eval_accuracy_high_school_geography": 0.9090909090909091,
164
- "mmlu_eval_accuracy_high_school_government_and_politics": 0.47619047619047616,
165
  "mmlu_eval_accuracy_high_school_macroeconomics": 0.4418604651162791,
166
  "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
167
- "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
168
  "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
169
- "mmlu_eval_accuracy_high_school_psychology": 0.85,
170
  "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
171
  "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
172
  "mmlu_eval_accuracy_high_school_world_history": 0.6923076923076923,
173
  "mmlu_eval_accuracy_human_aging": 0.782608695652174,
174
  "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
175
  "mmlu_eval_accuracy_international_law": 0.8461538461538461,
176
- "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
177
  "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
178
  "mmlu_eval_accuracy_machine_learning": 0.45454545454545453,
179
  "mmlu_eval_accuracy_management": 0.6363636363636364,
180
- "mmlu_eval_accuracy_marketing": 0.88,
181
  "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
182
  "mmlu_eval_accuracy_miscellaneous": 0.6627906976744186,
183
- "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
184
  "mmlu_eval_accuracy_moral_scenarios": 0.21,
185
- "mmlu_eval_accuracy_nutrition": 0.6666666666666666,
186
- "mmlu_eval_accuracy_philosophy": 0.5,
187
  "mmlu_eval_accuracy_prehistory": 0.5428571428571428,
188
- "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
189
- "mmlu_eval_accuracy_professional_law": 0.3176470588235294,
190
  "mmlu_eval_accuracy_professional_medicine": 0.5483870967741935,
191
- "mmlu_eval_accuracy_professional_psychology": 0.5072463768115942,
192
  "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
193
  "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
194
  "mmlu_eval_accuracy_sociology": 0.7272727272727273,
195
  "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
196
  "mmlu_eval_accuracy_virology": 0.5,
197
  "mmlu_eval_accuracy_world_religions": 0.6842105263157895,
198
- "mmlu_loss": 1.4345150615621174,
199
  "step": 200
200
  }
201
  ],
 
1
  {
2
+ "best_metric": 0.8420215845108032,
3
  "best_model_checkpoint": "experts/expert-22/checkpoint-200",
4
  "epoch": 0.0769897026272736,
5
  "global_step": 200,
 
10
  {
11
  "epoch": 0.0,
12
  "learning_rate": 0.0002,
13
+ "loss": 0.9409,
14
  "step": 10
15
  },
16
  {
17
  "epoch": 0.01,
18
  "learning_rate": 0.0002,
19
+ "loss": 0.9155,
20
  "step": 20
21
  },
22
  {
 
28
  {
29
  "epoch": 0.02,
30
  "learning_rate": 0.0002,
31
+ "loss": 0.8794,
32
  "step": 40
33
  },
34
  {
35
  "epoch": 0.02,
36
  "learning_rate": 0.0002,
37
+ "loss": 0.9277,
38
  "step": 50
39
  },
40
  {
41
  "epoch": 0.02,
42
  "learning_rate": 0.0002,
43
+ "loss": 0.864,
44
  "step": 60
45
  },
46
  {
47
  "epoch": 0.03,
48
  "learning_rate": 0.0002,
49
+ "loss": 0.953,
50
  "step": 70
51
  },
52
  {
 
64
  {
65
  "epoch": 0.04,
66
  "learning_rate": 0.0002,
67
+ "loss": 0.8647,
68
  "step": 100
69
  },
70
  {
71
  "epoch": 0.04,
72
  "learning_rate": 0.0002,
73
+ "loss": 0.9335,
74
  "step": 110
75
  },
76
  {
77
  "epoch": 0.05,
78
  "learning_rate": 0.0002,
79
+ "loss": 0.8879,
80
  "step": 120
81
  },
82
  {
83
  "epoch": 0.05,
84
  "learning_rate": 0.0002,
85
+ "loss": 0.8953,
86
  "step": 130
87
  },
88
  {
89
  "epoch": 0.05,
90
  "learning_rate": 0.0002,
91
+ "loss": 0.868,
92
  "step": 140
93
  },
94
  {
95
  "epoch": 0.06,
96
  "learning_rate": 0.0002,
97
+ "loss": 0.8585,
98
  "step": 150
99
  },
100
  {
101
  "epoch": 0.06,
102
  "learning_rate": 0.0002,
103
+ "loss": 0.8998,
104
  "step": 160
105
  },
106
  {
107
  "epoch": 0.07,
108
  "learning_rate": 0.0002,
109
+ "loss": 0.8672,
110
  "step": 170
111
  },
112
  {
113
  "epoch": 0.07,
114
  "learning_rate": 0.0002,
115
+ "loss": 0.8373,
116
  "step": 180
117
  },
118
  {
119
  "epoch": 0.07,
120
  "learning_rate": 0.0002,
121
+ "loss": 0.8492,
122
  "step": 190
123
  },
124
  {
125
  "epoch": 0.08,
126
  "learning_rate": 0.0002,
127
+ "loss": 0.8342,
128
  "step": 200
129
  },
130
  {
131
  "epoch": 0.08,
132
+ "eval_loss": 0.8420215845108032,
133
+ "eval_runtime": 77.6159,
134
+ "eval_samples_per_second": 12.884,
135
+ "eval_steps_per_second": 6.442,
136
  "step": 200
137
  },
138
  {
139
  "epoch": 0.08,
140
+ "mmlu_eval_accuracy": 0.5020690882678942,
141
  "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
142
  "mmlu_eval_accuracy_anatomy": 0.7142857142857143,
143
  "mmlu_eval_accuracy_astronomy": 0.4375,
144
  "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
145
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5517241379310345,
146
+ "mmlu_eval_accuracy_college_biology": 0.5,
147
  "mmlu_eval_accuracy_college_chemistry": 0.25,
148
  "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
149
  "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
150
  "mmlu_eval_accuracy_college_medicine": 0.36363636363636365,
151
  "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
152
  "mmlu_eval_accuracy_computer_security": 0.6363636363636364,
153
+ "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
154
  "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
155
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
156
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
157
  "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
158
  "mmlu_eval_accuracy_global_facts": 0.6,
159
+ "mmlu_eval_accuracy_high_school_biology": 0.53125,
160
  "mmlu_eval_accuracy_high_school_chemistry": 0.2727272727272727,
161
  "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
162
+ "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
163
  "mmlu_eval_accuracy_high_school_geography": 0.9090909090909091,
164
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5238095238095238,
165
  "mmlu_eval_accuracy_high_school_macroeconomics": 0.4418604651162791,
166
  "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
167
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
168
  "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
169
+ "mmlu_eval_accuracy_high_school_psychology": 0.8833333333333333,
170
  "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
171
  "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
172
  "mmlu_eval_accuracy_high_school_world_history": 0.6923076923076923,
173
  "mmlu_eval_accuracy_human_aging": 0.782608695652174,
174
  "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
175
  "mmlu_eval_accuracy_international_law": 0.8461538461538461,
176
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
177
  "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
178
  "mmlu_eval_accuracy_machine_learning": 0.45454545454545453,
179
  "mmlu_eval_accuracy_management": 0.6363636363636364,
180
+ "mmlu_eval_accuracy_marketing": 0.84,
181
  "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
182
  "mmlu_eval_accuracy_miscellaneous": 0.6627906976744186,
183
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
184
  "mmlu_eval_accuracy_moral_scenarios": 0.21,
185
+ "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
186
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
187
  "mmlu_eval_accuracy_prehistory": 0.5428571428571428,
188
+ "mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
189
+ "mmlu_eval_accuracy_professional_law": 0.3235294117647059,
190
  "mmlu_eval_accuracy_professional_medicine": 0.5483870967741935,
191
+ "mmlu_eval_accuracy_professional_psychology": 0.4782608695652174,
192
  "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
193
  "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
194
  "mmlu_eval_accuracy_sociology": 0.7272727272727273,
195
  "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
196
  "mmlu_eval_accuracy_virology": 0.5,
197
  "mmlu_eval_accuracy_world_religions": 0.6842105263157895,
198
+ "mmlu_loss": 1.42281840854463,
199
  "step": 200
200
  }
201
  ],
checkpoint-200/training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:68347c5c0bc67308405eaf249524c55462e787942d6d74b927105955b931cf02
3
  size 5819
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:376563167fb75ef06e6c8600f9d035897ffea2363fc5fd45e427161c33ec50e3
3
  size 5819
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:68347c5c0bc67308405eaf249524c55462e787942d6d74b927105955b931cf02
3
  size 5819
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:376563167fb75ef06e6c8600f9d035897ffea2363fc5fd45e427161c33ec50e3
3
  size 5819