gokulsrinivasagan commited on
Commit
4115e17
·
verified ·
1 Parent(s): b0b7932

End of training

Browse files
README.md CHANGED
@@ -1,14 +1,29 @@
1
  ---
2
  library_name: transformers
 
 
3
  license: apache-2.0
4
  base_model: gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init
5
  tags:
6
  - generated_from_trainer
 
 
7
  metrics:
8
  - accuracy
9
  model-index:
10
  - name: tinybert_base_train_book_ent_15p_s_init_mnli
11
- results: []
 
 
 
 
 
 
 
 
 
 
 
12
  ---
13
 
14
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,10 +31,10 @@ should probably proofread and complete it, then remove this comment. -->
16
 
17
  # tinybert_base_train_book_ent_15p_s_init_mnli
18
 
19
- This model is a fine-tuned version of [gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init](https://huggingface.co/gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init) on an unknown dataset.
20
  It achieves the following results on the evaluation set:
21
- - Loss: 0.8376
22
- - Accuracy: 0.7220
23
 
24
  ## Model description
25
 
 
1
  ---
2
  library_name: transformers
3
+ language:
4
+ - en
5
  license: apache-2.0
6
  base_model: gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init
7
  tags:
8
  - generated_from_trainer
9
+ datasets:
10
+ - glue
11
  metrics:
12
  - accuracy
13
  model-index:
14
  - name: tinybert_base_train_book_ent_15p_s_init_mnli
15
+ results:
16
+ - task:
17
+ name: Text Classification
18
+ type: text-classification
19
+ dataset:
20
+ name: GLUE MNLI
21
+ type: glue
22
+ args: mnli
23
+ metrics:
24
+ - name: Accuracy
25
+ type: accuracy
26
+ value: 0.725386493083808
27
  ---
28
 
29
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
31
 
32
  # tinybert_base_train_book_ent_15p_s_init_mnli
33
 
34
+ This model is a fine-tuned version of [gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init](https://huggingface.co/gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init) on the GLUE MNLI dataset.
35
  It achieves the following results on the evaluation set:
36
+ - Loss: 0.6549
37
+ - Accuracy: 0.7254
38
 
39
  ## Model description
40
 
all_results.json ADDED
@@ -0,0 +1,22 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "epoch": 10.0,
3
+ "epoch_mm": 10.0,
4
+ "eval_accuracy": 0.7245033112582782,
5
+ "eval_accuracy_mm": 0.725386493083808,
6
+ "eval_loss": 0.6811214685440063,
7
+ "eval_loss_mm": 0.6549021601676941,
8
+ "eval_runtime": 5.3427,
9
+ "eval_runtime_mm": 5.2794,
10
+ "eval_samples": 9815,
11
+ "eval_samples_mm": 9832,
12
+ "eval_samples_per_second": 1837.09,
13
+ "eval_samples_per_second_mm": 1862.335,
14
+ "eval_steps_per_second": 7.3,
15
+ "eval_steps_per_second_mm": 7.387,
16
+ "total_flos": 7.76592697038336e+16,
17
+ "train_loss": 0.5669185474301255,
18
+ "train_runtime": 2952.0721,
19
+ "train_samples": 392702,
20
+ "train_samples_per_second": 6651.294,
21
+ "train_steps_per_second": 25.982
22
+ }
eval_results.json ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "epoch": 10.0,
3
+ "epoch_mm": 10.0,
4
+ "eval_accuracy": 0.7245033112582782,
5
+ "eval_accuracy_mm": 0.725386493083808,
6
+ "eval_loss": 0.6811214685440063,
7
+ "eval_loss_mm": 0.6549021601676941,
8
+ "eval_runtime": 5.3427,
9
+ "eval_runtime_mm": 5.2794,
10
+ "eval_samples": 9815,
11
+ "eval_samples_mm": 9832,
12
+ "eval_samples_per_second": 1837.09,
13
+ "eval_samples_per_second_mm": 1862.335,
14
+ "eval_steps_per_second": 7.3,
15
+ "eval_steps_per_second_mm": 7.387
16
+ }
logs/events.out.tfevents.1745511304.ki-g0008.3436350.17 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e1e9c1c47a67d5e9d2153cb3bde5cdadea0d1e7b81d16756d485424d5b9a17b0
3
+ size 734
train_results.json ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "epoch": 10.0,
3
+ "total_flos": 7.76592697038336e+16,
4
+ "train_loss": 0.5669185474301255,
5
+ "train_runtime": 2952.0721,
6
+ "train_samples": 392702,
7
+ "train_samples_per_second": 6651.294,
8
+ "train_steps_per_second": 25.982
9
+ }
trainer_state.json ADDED
@@ -0,0 +1,212 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": 7670,
3
+ "best_metric": 0.6811214685440063,
4
+ "best_model_checkpoint": "tinybert_base_train_book_ent_15p_s_init_mnli/checkpoint-7670",
5
+ "epoch": 10.0,
6
+ "eval_steps": 500,
7
+ "global_step": 15340,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 1.0,
14
+ "grad_norm": 1.6886646747589111,
15
+ "learning_rate": 4.90006518904824e-05,
16
+ "loss": 0.8785,
17
+ "step": 1534
18
+ },
19
+ {
20
+ "epoch": 1.0,
21
+ "eval_accuracy": 0.6660213958227204,
22
+ "eval_loss": 0.7728874087333679,
23
+ "eval_runtime": 5.2916,
24
+ "eval_samples_per_second": 1854.821,
25
+ "eval_steps_per_second": 7.37,
26
+ "step": 1534
27
+ },
28
+ {
29
+ "epoch": 2.0,
30
+ "grad_norm": 1.5701472759246826,
31
+ "learning_rate": 4.80006518904824e-05,
32
+ "loss": 0.7353,
33
+ "step": 3068
34
+ },
35
+ {
36
+ "epoch": 2.0,
37
+ "eval_accuracy": 0.691492613346918,
38
+ "eval_loss": 0.7123497724533081,
39
+ "eval_runtime": 5.2657,
40
+ "eval_samples_per_second": 1863.958,
41
+ "eval_steps_per_second": 7.406,
42
+ "step": 3068
43
+ },
44
+ {
45
+ "epoch": 3.0,
46
+ "grad_norm": 1.9975154399871826,
47
+ "learning_rate": 4.70006518904824e-05,
48
+ "loss": 0.6658,
49
+ "step": 4602
50
+ },
51
+ {
52
+ "epoch": 3.0,
53
+ "eval_accuracy": 0.7072847682119205,
54
+ "eval_loss": 0.6983441710472107,
55
+ "eval_runtime": 5.2335,
56
+ "eval_samples_per_second": 1875.435,
57
+ "eval_steps_per_second": 7.452,
58
+ "step": 4602
59
+ },
60
+ {
61
+ "epoch": 4.0,
62
+ "grad_norm": 2.1961188316345215,
63
+ "learning_rate": 4.60006518904824e-05,
64
+ "loss": 0.6113,
65
+ "step": 6136
66
+ },
67
+ {
68
+ "epoch": 4.0,
69
+ "eval_accuracy": 0.7168619460010188,
70
+ "eval_loss": 0.700081467628479,
71
+ "eval_runtime": 5.2018,
72
+ "eval_samples_per_second": 1886.83,
73
+ "eval_steps_per_second": 7.497,
74
+ "step": 6136
75
+ },
76
+ {
77
+ "epoch": 5.0,
78
+ "grad_norm": 2.4144446849823,
79
+ "learning_rate": 4.50006518904824e-05,
80
+ "loss": 0.5654,
81
+ "step": 7670
82
+ },
83
+ {
84
+ "epoch": 5.0,
85
+ "eval_accuracy": 0.7245033112582782,
86
+ "eval_loss": 0.6811214685440063,
87
+ "eval_runtime": 5.2441,
88
+ "eval_samples_per_second": 1871.624,
89
+ "eval_steps_per_second": 7.437,
90
+ "step": 7670
91
+ },
92
+ {
93
+ "epoch": 6.0,
94
+ "grad_norm": 2.4327688217163086,
95
+ "learning_rate": 4.40006518904824e-05,
96
+ "loss": 0.5207,
97
+ "step": 9204
98
+ },
99
+ {
100
+ "epoch": 6.0,
101
+ "eval_accuracy": 0.7257259296994396,
102
+ "eval_loss": 0.7057485580444336,
103
+ "eval_runtime": 5.236,
104
+ "eval_samples_per_second": 1874.515,
105
+ "eval_steps_per_second": 7.448,
106
+ "step": 9204
107
+ },
108
+ {
109
+ "epoch": 7.0,
110
+ "grad_norm": 2.349059581756592,
111
+ "learning_rate": 4.30006518904824e-05,
112
+ "loss": 0.4798,
113
+ "step": 10738
114
+ },
115
+ {
116
+ "epoch": 7.0,
117
+ "eval_accuracy": 0.7290881304126338,
118
+ "eval_loss": 0.7188459038734436,
119
+ "eval_runtime": 5.2738,
120
+ "eval_samples_per_second": 1861.082,
121
+ "eval_steps_per_second": 7.395,
122
+ "step": 10738
123
+ },
124
+ {
125
+ "epoch": 8.0,
126
+ "grad_norm": 3.1730854511260986,
127
+ "learning_rate": 4.20006518904824e-05,
128
+ "loss": 0.4403,
129
+ "step": 12272
130
+ },
131
+ {
132
+ "epoch": 8.0,
133
+ "eval_accuracy": 0.7230769230769231,
134
+ "eval_loss": 0.7684288024902344,
135
+ "eval_runtime": 5.2321,
136
+ "eval_samples_per_second": 1875.918,
137
+ "eval_steps_per_second": 7.454,
138
+ "step": 12272
139
+ },
140
+ {
141
+ "epoch": 9.0,
142
+ "grad_norm": 3.504354953765869,
143
+ "learning_rate": 4.10006518904824e-05,
144
+ "loss": 0.4036,
145
+ "step": 13806
146
+ },
147
+ {
148
+ "epoch": 9.0,
149
+ "eval_accuracy": 0.7164544065206316,
150
+ "eval_loss": 0.8033895492553711,
151
+ "eval_runtime": 5.2638,
152
+ "eval_samples_per_second": 1864.638,
153
+ "eval_steps_per_second": 7.409,
154
+ "step": 13806
155
+ },
156
+ {
157
+ "epoch": 10.0,
158
+ "grad_norm": 3.7538444995880127,
159
+ "learning_rate": 4.00006518904824e-05,
160
+ "loss": 0.3685,
161
+ "step": 15340
162
+ },
163
+ {
164
+ "epoch": 10.0,
165
+ "eval_accuracy": 0.7219561895058584,
166
+ "eval_loss": 0.837572455406189,
167
+ "eval_runtime": 5.2382,
168
+ "eval_samples_per_second": 1873.732,
169
+ "eval_steps_per_second": 7.445,
170
+ "step": 15340
171
+ },
172
+ {
173
+ "epoch": 10.0,
174
+ "step": 15340,
175
+ "total_flos": 7.76592697038336e+16,
176
+ "train_loss": 0.5669185474301255,
177
+ "train_runtime": 2952.0721,
178
+ "train_samples_per_second": 6651.294,
179
+ "train_steps_per_second": 25.982
180
+ }
181
+ ],
182
+ "logging_steps": 1,
183
+ "max_steps": 76700,
184
+ "num_input_tokens_seen": 0,
185
+ "num_train_epochs": 50,
186
+ "save_steps": 500,
187
+ "stateful_callbacks": {
188
+ "EarlyStoppingCallback": {
189
+ "args": {
190
+ "early_stopping_patience": 5,
191
+ "early_stopping_threshold": 0.0
192
+ },
193
+ "attributes": {
194
+ "early_stopping_patience_counter": 5
195
+ }
196
+ },
197
+ "TrainerControl": {
198
+ "args": {
199
+ "should_epoch_stop": false,
200
+ "should_evaluate": false,
201
+ "should_log": false,
202
+ "should_save": true,
203
+ "should_training_stop": true
204
+ },
205
+ "attributes": {}
206
+ }
207
+ },
208
+ "total_flos": 7.76592697038336e+16,
209
+ "train_batch_size": 256,
210
+ "trial_name": null,
211
+ "trial_params": null
212
+ }