abdouaziiz commited on
Commit
e551c7a
1 Parent(s): a412f63

Upload 6 files

Browse files
README.md ADDED
@@ -0,0 +1,97 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - audio-classification
5
+ - generated_from_trainer
6
+ metrics:
7
+ - accuracy
8
+ - precision
9
+ - f1
10
+ model-index:
11
+ - name: hubert-large-ls960-ft
12
+ results: []
13
+ ---
14
+
15
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
16
+ should probably proofread and complete it, then remove this comment. -->
17
+
18
+ # hubert-large-ls960-ft
19
+
20
+ This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the galsenai/waxal_dataset dataset.
21
+ It achieves the following results on the evaluation set:
22
+ - Loss: 0.3272
23
+ - Accuracy: 0.9413
24
+ - Precision: 0.9865
25
+ - F1: 0.9628
26
+
27
+ ## Model description
28
+
29
+ More information needed
30
+
31
+ ## Intended uses & limitations
32
+
33
+ More information needed
34
+
35
+ ## Training and evaluation data
36
+
37
+ More information needed
38
+
39
+ ## Training procedure
40
+
41
+ ### Training hyperparameters
42
+
43
+ The following hyperparameters were used during training:
44
+ - learning_rate: 3e-05
45
+ - train_batch_size: 12
46
+ - eval_batch_size: 12
47
+ - seed: 0
48
+ - gradient_accumulation_steps: 4
49
+ - total_train_batch_size: 48
50
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
51
+ - lr_scheduler_type: linear
52
+ - lr_scheduler_warmup_ratio: 0.1
53
+ - num_epochs: 32.0
54
+
55
+ ### Training results
56
+
57
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | F1 |
58
+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|
59
+ | 4.7142 | 1.01 | 500 | 5.2765 | 0.0 | 0.0 | 0.0 |
60
+ | 4.396 | 2.02 | 1000 | 5.4145 | 0.0 | 0.0 | 0.0 |
61
+ | 3.8883 | 3.04 | 1500 | 4.4336 | 0.0474 | 0.0408 | 0.0104 |
62
+ | 2.7848 | 4.05 | 2000 | 3.9772 | 0.1300 | 0.1281 | 0.0964 |
63
+ | 1.8649 | 5.06 | 2500 | 3.4482 | 0.1576 | 0.3339 | 0.1547 |
64
+ | 1.3084 | 6.07 | 3000 | 2.9703 | 0.3081 | 0.5296 | 0.3402 |
65
+ | 0.9868 | 7.08 | 3500 | 2.3985 | 0.4687 | 0.8032 | 0.5353 |
66
+ | 0.7679 | 8.1 | 4000 | 1.7937 | 0.6521 | 0.8389 | 0.7095 |
67
+ | 0.6232 | 9.11 | 4500 | 1.4768 | 0.7389 | 0.8698 | 0.7847 |
68
+ | 0.5126 | 10.12 | 5000 | 1.0542 | 0.8287 | 0.9443 | 0.8763 |
69
+ | 0.4453 | 11.13 | 5500 | 0.9050 | 0.8518 | 0.9511 | 0.8960 |
70
+ | 0.3775 | 12.15 | 6000 | 0.6996 | 0.8928 | 0.9662 | 0.9266 |
71
+ | 0.3568 | 13.16 | 6500 | 0.6157 | 0.8958 | 0.9743 | 0.9285 |
72
+ | 0.3165 | 14.17 | 7000 | 0.4925 | 0.9151 | 0.9764 | 0.9436 |
73
+ | 0.2951 | 15.18 | 7500 | 0.4992 | 0.9038 | 0.9773 | 0.9369 |
74
+ | 0.2763 | 16.19 | 8000 | 0.5212 | 0.9072 | 0.9821 | 0.9404 |
75
+ | 0.2634 | 17.21 | 8500 | 0.5201 | 0.9087 | 0.9817 | 0.9418 |
76
+ | 0.2422 | 18.22 | 9000 | 0.4504 | 0.9235 | 0.9840 | 0.9514 |
77
+ | 0.236 | 19.23 | 9500 | 0.3829 | 0.9257 | 0.9825 | 0.9518 |
78
+ | 0.2272 | 20.24 | 10000 | 0.4632 | 0.9155 | 0.9822 | 0.9451 |
79
+ | 0.226 | 21.25 | 10500 | 0.4731 | 0.9159 | 0.9837 | 0.9470 |
80
+ | 0.2129 | 22.27 | 11000 | 0.3814 | 0.9299 | 0.9832 | 0.9549 |
81
+ | 0.2009 | 23.28 | 11500 | 0.4119 | 0.9257 | 0.9814 | 0.9515 |
82
+ | 0.1973 | 24.29 | 12000 | 0.4310 | 0.9216 | 0.9843 | 0.9493 |
83
+ | 0.1965 | 25.3 | 12500 | 0.3272 | 0.9413 | 0.9865 | 0.9628 |
84
+ | 0.1989 | 26.32 | 13000 | 0.4231 | 0.9242 | 0.9878 | 0.9528 |
85
+ | 0.1916 | 27.33 | 13500 | 0.3978 | 0.9284 | 0.9876 | 0.9559 |
86
+ | 0.1849 | 28.34 | 14000 | 0.4529 | 0.9216 | 0.9865 | 0.9507 |
87
+ | 0.1844 | 29.35 | 14500 | 0.3854 | 0.9314 | 0.9864 | 0.9566 |
88
+ | 0.1831 | 30.36 | 15000 | 0.4178 | 0.9257 | 0.9853 | 0.9528 |
89
+ | 0.1778 | 31.38 | 15500 | 0.3737 | 0.9360 | 0.9884 | 0.9606 |
90
+
91
+
92
+ ### Framework versions
93
+
94
+ - Transformers 4.27.0.dev0
95
+ - Pytorch 1.11.0+cu113
96
+ - Datasets 2.9.1.dev0
97
+ - Tokenizers 0.13.2
all_results.json ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "epoch": 32.0,
3
+ "eval_accuracy": 0.9412656309208033,
4
+ "eval_f1": 0.9627712250405202,
5
+ "eval_loss": 0.327240914106369,
6
+ "eval_precision": 0.9865248931670977,
7
+ "eval_runtime": 205.0233,
8
+ "eval_samples_per_second": 12.872,
9
+ "eval_steps_per_second": 1.073,
10
+ "train_loss": 0.858633176759187,
11
+ "train_runtime": 80385.1912,
12
+ "train_samples_per_second": 9.454,
13
+ "train_steps_per_second": 0.197
14
+ }
eval_results.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "epoch": 32.0,
3
+ "eval_accuracy": 0.9412656309208033,
4
+ "eval_f1": 0.9627712250405202,
5
+ "eval_loss": 0.327240914106369,
6
+ "eval_precision": 0.9865248931670977,
7
+ "eval_runtime": 205.0233,
8
+ "eval_samples_per_second": 12.872,
9
+ "eval_steps_per_second": 1.073
10
+ }
train_results.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ {
2
+ "epoch": 32.0,
3
+ "train_loss": 0.858633176759187,
4
+ "train_runtime": 80385.1912,
5
+ "train_samples_per_second": 9.454,
6
+ "train_steps_per_second": 0.197
7
+ }
trainer_state.json ADDED
@@ -0,0 +1,552 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 0.9412656309208033,
3
+ "best_model_checkpoint": "hubert-large-ls960-ft/checkpoint-12500",
4
+ "epoch": 31.998484082870135,
5
+ "global_step": 15808,
6
+ "is_hyper_param_search": false,
7
+ "is_local_process_zero": true,
8
+ "is_world_process_zero": true,
9
+ "log_history": [
10
+ {
11
+ "epoch": 1.01,
12
+ "learning_rate": 9.487666034155598e-06,
13
+ "loss": 4.7142,
14
+ "step": 500
15
+ },
16
+ {
17
+ "epoch": 1.01,
18
+ "eval_accuracy": 0.0,
19
+ "eval_f1": 0.0,
20
+ "eval_loss": 5.276514053344727,
21
+ "eval_precision": 0.0,
22
+ "eval_runtime": 207.9912,
23
+ "eval_samples_per_second": 12.688,
24
+ "eval_steps_per_second": 1.058,
25
+ "step": 500
26
+ },
27
+ {
28
+ "epoch": 2.02,
29
+ "learning_rate": 1.8975332068311197e-05,
30
+ "loss": 4.396,
31
+ "step": 1000
32
+ },
33
+ {
34
+ "epoch": 2.02,
35
+ "eval_accuracy": 0.0,
36
+ "eval_f1": 0.0,
37
+ "eval_loss": 5.414546012878418,
38
+ "eval_precision": 0.0,
39
+ "eval_runtime": 211.3332,
40
+ "eval_samples_per_second": 12.487,
41
+ "eval_steps_per_second": 1.041,
42
+ "step": 1000
43
+ },
44
+ {
45
+ "epoch": 3.04,
46
+ "learning_rate": 2.846299810246679e-05,
47
+ "loss": 3.8883,
48
+ "step": 1500
49
+ },
50
+ {
51
+ "epoch": 3.04,
52
+ "eval_accuracy": 0.0473664266767715,
53
+ "eval_f1": 0.010399469379098707,
54
+ "eval_loss": 4.433555603027344,
55
+ "eval_precision": 0.04084585694141838,
56
+ "eval_runtime": 206.03,
57
+ "eval_samples_per_second": 12.809,
58
+ "eval_steps_per_second": 1.068,
59
+ "step": 1500
60
+ },
61
+ {
62
+ "epoch": 4.05,
63
+ "learning_rate": 2.9116468686300697e-05,
64
+ "loss": 2.7848,
65
+ "step": 2000
66
+ },
67
+ {
68
+ "epoch": 4.05,
69
+ "eval_accuracy": 0.129973474801061,
70
+ "eval_f1": 0.09643252305766986,
71
+ "eval_loss": 3.9772207736968994,
72
+ "eval_precision": 0.1280919938791079,
73
+ "eval_runtime": 212.3184,
74
+ "eval_samples_per_second": 12.429,
75
+ "eval_steps_per_second": 1.036,
76
+ "step": 2000
77
+ },
78
+ {
79
+ "epoch": 5.06,
80
+ "learning_rate": 2.8062135376396992e-05,
81
+ "loss": 1.8649,
82
+ "step": 2500
83
+ },
84
+ {
85
+ "epoch": 5.06,
86
+ "eval_accuracy": 0.15763546798029557,
87
+ "eval_f1": 0.15466013987384877,
88
+ "eval_loss": 3.44816255569458,
89
+ "eval_precision": 0.33391187818919965,
90
+ "eval_runtime": 206.6675,
91
+ "eval_samples_per_second": 12.769,
92
+ "eval_steps_per_second": 1.065,
93
+ "step": 2500
94
+ },
95
+ {
96
+ "epoch": 6.07,
97
+ "learning_rate": 2.700780206649329e-05,
98
+ "loss": 1.3084,
99
+ "step": 3000
100
+ },
101
+ {
102
+ "epoch": 6.07,
103
+ "eval_accuracy": 0.3080712391057219,
104
+ "eval_f1": 0.3402390216080642,
105
+ "eval_loss": 2.9702537059783936,
106
+ "eval_precision": 0.5296031035295795,
107
+ "eval_runtime": 212.8576,
108
+ "eval_samples_per_second": 12.398,
109
+ "eval_steps_per_second": 1.034,
110
+ "step": 3000
111
+ },
112
+ {
113
+ "epoch": 7.08,
114
+ "learning_rate": 2.5953468756589585e-05,
115
+ "loss": 0.9868,
116
+ "step": 3500
117
+ },
118
+ {
119
+ "epoch": 7.08,
120
+ "eval_accuracy": 0.46873815839333083,
121
+ "eval_f1": 0.5353322629682942,
122
+ "eval_loss": 2.3984930515289307,
123
+ "eval_precision": 0.8031566212997642,
124
+ "eval_runtime": 207.1643,
125
+ "eval_samples_per_second": 12.739,
126
+ "eval_steps_per_second": 1.062,
127
+ "step": 3500
128
+ },
129
+ {
130
+ "epoch": 8.1,
131
+ "learning_rate": 2.489913544668588e-05,
132
+ "loss": 0.7679,
133
+ "step": 4000
134
+ },
135
+ {
136
+ "epoch": 8.1,
137
+ "eval_accuracy": 0.6521409624857901,
138
+ "eval_f1": 0.7095065774545717,
139
+ "eval_loss": 1.7936781644821167,
140
+ "eval_precision": 0.8388581448735327,
141
+ "eval_runtime": 207.3219,
142
+ "eval_samples_per_second": 12.729,
143
+ "eval_steps_per_second": 1.061,
144
+ "step": 4000
145
+ },
146
+ {
147
+ "epoch": 9.11,
148
+ "learning_rate": 2.3844802136782175e-05,
149
+ "loss": 0.6232,
150
+ "step": 4500
151
+ },
152
+ {
153
+ "epoch": 9.11,
154
+ "eval_accuracy": 0.7389162561576355,
155
+ "eval_f1": 0.784666736405717,
156
+ "eval_loss": 1.4767512083053589,
157
+ "eval_precision": 0.8697758947640245,
158
+ "eval_runtime": 211.7813,
159
+ "eval_samples_per_second": 12.461,
160
+ "eval_steps_per_second": 1.039,
161
+ "step": 4500
162
+ },
163
+ {
164
+ "epoch": 10.12,
165
+ "learning_rate": 2.279046882687847e-05,
166
+ "loss": 0.5126,
167
+ "step": 5000
168
+ },
169
+ {
170
+ "epoch": 10.12,
171
+ "eval_accuracy": 0.8287230011367942,
172
+ "eval_f1": 0.8762583534303519,
173
+ "eval_loss": 1.054182529449463,
174
+ "eval_precision": 0.9442564310504037,
175
+ "eval_runtime": 210.7585,
176
+ "eval_samples_per_second": 12.521,
177
+ "eval_steps_per_second": 1.044,
178
+ "step": 5000
179
+ },
180
+ {
181
+ "epoch": 11.13,
182
+ "learning_rate": 2.1736135516974768e-05,
183
+ "loss": 0.4453,
184
+ "step": 5500
185
+ },
186
+ {
187
+ "epoch": 11.13,
188
+ "eval_accuracy": 0.8518378173550587,
189
+ "eval_f1": 0.8959895568662314,
190
+ "eval_loss": 0.9049583673477173,
191
+ "eval_precision": 0.9511477433978877,
192
+ "eval_runtime": 205.4589,
193
+ "eval_samples_per_second": 12.844,
194
+ "eval_steps_per_second": 1.071,
195
+ "step": 5500
196
+ },
197
+ {
198
+ "epoch": 12.15,
199
+ "learning_rate": 2.0681802207071063e-05,
200
+ "loss": 0.3775,
201
+ "step": 6000
202
+ },
203
+ {
204
+ "epoch": 12.15,
205
+ "eval_accuracy": 0.8927624100037893,
206
+ "eval_f1": 0.9265578308615539,
207
+ "eval_loss": 0.699573278427124,
208
+ "eval_precision": 0.9662252548898577,
209
+ "eval_runtime": 212.4773,
210
+ "eval_samples_per_second": 12.42,
211
+ "eval_steps_per_second": 1.035,
212
+ "step": 6000
213
+ },
214
+ {
215
+ "epoch": 13.16,
216
+ "learning_rate": 1.9627468897167357e-05,
217
+ "loss": 0.3568,
218
+ "step": 6500
219
+ },
220
+ {
221
+ "epoch": 13.16,
222
+ "eval_accuracy": 0.8957938613111027,
223
+ "eval_f1": 0.9284579551378114,
224
+ "eval_loss": 0.6156648993492126,
225
+ "eval_precision": 0.9743169949637361,
226
+ "eval_runtime": 210.2311,
227
+ "eval_samples_per_second": 12.553,
228
+ "eval_steps_per_second": 1.046,
229
+ "step": 6500
230
+ },
231
+ {
232
+ "epoch": 14.17,
233
+ "learning_rate": 1.8573135587263652e-05,
234
+ "loss": 0.3165,
235
+ "step": 7000
236
+ },
237
+ {
238
+ "epoch": 14.17,
239
+ "eval_accuracy": 0.9151193633952255,
240
+ "eval_f1": 0.943623023847651,
241
+ "eval_loss": 0.4924512505531311,
242
+ "eval_precision": 0.9763736094436646,
243
+ "eval_runtime": 206.0776,
244
+ "eval_samples_per_second": 12.806,
245
+ "eval_steps_per_second": 1.068,
246
+ "step": 7000
247
+ },
248
+ {
249
+ "epoch": 15.18,
250
+ "learning_rate": 1.751880227735995e-05,
251
+ "loss": 0.2951,
252
+ "step": 7500
253
+ },
254
+ {
255
+ "epoch": 15.18,
256
+ "eval_accuracy": 0.9037514209928003,
257
+ "eval_f1": 0.9368584519497015,
258
+ "eval_loss": 0.49918055534362793,
259
+ "eval_precision": 0.9772932630240506,
260
+ "eval_runtime": 205.4956,
261
+ "eval_samples_per_second": 12.842,
262
+ "eval_steps_per_second": 1.071,
263
+ "step": 7500
264
+ },
265
+ {
266
+ "epoch": 16.19,
267
+ "learning_rate": 1.6464468967456245e-05,
268
+ "loss": 0.2763,
269
+ "step": 8000
270
+ },
271
+ {
272
+ "epoch": 16.19,
273
+ "eval_accuracy": 0.9071618037135278,
274
+ "eval_f1": 0.9403855453166055,
275
+ "eval_loss": 0.5212343335151672,
276
+ "eval_precision": 0.9820562398022753,
277
+ "eval_runtime": 211.5185,
278
+ "eval_samples_per_second": 12.476,
279
+ "eval_steps_per_second": 1.04,
280
+ "step": 8000
281
+ },
282
+ {
283
+ "epoch": 17.21,
284
+ "learning_rate": 1.541013565755254e-05,
285
+ "loss": 0.2634,
286
+ "step": 8500
287
+ },
288
+ {
289
+ "epoch": 17.21,
290
+ "eval_accuracy": 0.9086775293671845,
291
+ "eval_f1": 0.9417778927796274,
292
+ "eval_loss": 0.5201326012611389,
293
+ "eval_precision": 0.9816838665228488,
294
+ "eval_runtime": 205.8774,
295
+ "eval_samples_per_second": 12.818,
296
+ "eval_steps_per_second": 1.069,
297
+ "step": 8500
298
+ },
299
+ {
300
+ "epoch": 18.22,
301
+ "learning_rate": 1.4355802347648837e-05,
302
+ "loss": 0.2422,
303
+ "step": 9000
304
+ },
305
+ {
306
+ "epoch": 18.22,
307
+ "eval_accuracy": 0.9234558544903373,
308
+ "eval_f1": 0.9514314684994079,
309
+ "eval_loss": 0.45036178827285767,
310
+ "eval_precision": 0.9839863223736393,
311
+ "eval_runtime": 211.5273,
312
+ "eval_samples_per_second": 12.476,
313
+ "eval_steps_per_second": 1.04,
314
+ "step": 9000
315
+ },
316
+ {
317
+ "epoch": 19.23,
318
+ "learning_rate": 1.3301469037745133e-05,
319
+ "loss": 0.236,
320
+ "step": 9500
321
+ },
322
+ {
323
+ "epoch": 19.23,
324
+ "eval_accuracy": 0.9257294429708223,
325
+ "eval_f1": 0.9518288569523149,
326
+ "eval_loss": 0.3829096853733063,
327
+ "eval_precision": 0.9824861532841103,
328
+ "eval_runtime": 210.8744,
329
+ "eval_samples_per_second": 12.515,
330
+ "eval_steps_per_second": 1.043,
331
+ "step": 9500
332
+ },
333
+ {
334
+ "epoch": 20.24,
335
+ "learning_rate": 1.2247135727841428e-05,
336
+ "loss": 0.2272,
337
+ "step": 10000
338
+ },
339
+ {
340
+ "epoch": 20.24,
341
+ "eval_accuracy": 0.9154982948086396,
342
+ "eval_f1": 0.9451193658066668,
343
+ "eval_loss": 0.4632132947444916,
344
+ "eval_precision": 0.9822249030180286,
345
+ "eval_runtime": 207.0475,
346
+ "eval_samples_per_second": 12.746,
347
+ "eval_steps_per_second": 1.063,
348
+ "step": 10000
349
+ },
350
+ {
351
+ "epoch": 21.25,
352
+ "learning_rate": 1.1192802417937724e-05,
353
+ "loss": 0.226,
354
+ "step": 10500
355
+ },
356
+ {
357
+ "epoch": 21.25,
358
+ "eval_accuracy": 0.9158772262220538,
359
+ "eval_f1": 0.947028332160647,
360
+ "eval_loss": 0.47312408685684204,
361
+ "eval_precision": 0.9837188228053231,
362
+ "eval_runtime": 210.5001,
363
+ "eval_samples_per_second": 12.537,
364
+ "eval_steps_per_second": 1.045,
365
+ "step": 10500
366
+ },
367
+ {
368
+ "epoch": 22.27,
369
+ "learning_rate": 1.013846910803402e-05,
370
+ "loss": 0.2129,
371
+ "step": 11000
372
+ },
373
+ {
374
+ "epoch": 22.27,
375
+ "eval_accuracy": 0.9298976885183782,
376
+ "eval_f1": 0.9548846481808738,
377
+ "eval_loss": 0.38141778111457825,
378
+ "eval_precision": 0.983160805693422,
379
+ "eval_runtime": 210.7476,
380
+ "eval_samples_per_second": 12.522,
381
+ "eval_steps_per_second": 1.044,
382
+ "step": 11000
383
+ },
384
+ {
385
+ "epoch": 23.28,
386
+ "learning_rate": 9.084135798130316e-06,
387
+ "loss": 0.2009,
388
+ "step": 11500
389
+ },
390
+ {
391
+ "epoch": 23.28,
392
+ "eval_accuracy": 0.9257294429708223,
393
+ "eval_f1": 0.9514840419100091,
394
+ "eval_loss": 0.4119464159011841,
395
+ "eval_precision": 0.9814366336318854,
396
+ "eval_runtime": 206.3284,
397
+ "eval_samples_per_second": 12.79,
398
+ "eval_steps_per_second": 1.066,
399
+ "step": 11500
400
+ },
401
+ {
402
+ "epoch": 24.29,
403
+ "learning_rate": 8.029802488226612e-06,
404
+ "loss": 0.1973,
405
+ "step": 12000
406
+ },
407
+ {
408
+ "epoch": 24.29,
409
+ "eval_accuracy": 0.9215611974232664,
410
+ "eval_f1": 0.9492716683321308,
411
+ "eval_loss": 0.43100807070732117,
412
+ "eval_precision": 0.98427363081955,
413
+ "eval_runtime": 210.5932,
414
+ "eval_samples_per_second": 12.531,
415
+ "eval_steps_per_second": 1.045,
416
+ "step": 12000
417
+ },
418
+ {
419
+ "epoch": 25.3,
420
+ "learning_rate": 6.975469178322908e-06,
421
+ "loss": 0.1965,
422
+ "step": 12500
423
+ },
424
+ {
425
+ "epoch": 25.3,
426
+ "eval_accuracy": 0.9412656309208033,
427
+ "eval_f1": 0.9627712250405202,
428
+ "eval_loss": 0.327240914106369,
429
+ "eval_precision": 0.9865248931670977,
430
+ "eval_runtime": 207.1296,
431
+ "eval_samples_per_second": 12.741,
432
+ "eval_steps_per_second": 1.062,
433
+ "step": 12500
434
+ },
435
+ {
436
+ "epoch": 26.32,
437
+ "learning_rate": 5.9211358684192026e-06,
438
+ "loss": 0.1989,
439
+ "step": 13000
440
+ },
441
+ {
442
+ "epoch": 26.32,
443
+ "eval_accuracy": 0.9242137173171656,
444
+ "eval_f1": 0.9527761591577618,
445
+ "eval_loss": 0.4231082797050476,
446
+ "eval_precision": 0.9877979282330233,
447
+ "eval_runtime": 212.06,
448
+ "eval_samples_per_second": 12.445,
449
+ "eval_steps_per_second": 1.037,
450
+ "step": 13000
451
+ },
452
+ {
453
+ "epoch": 27.33,
454
+ "learning_rate": 4.866802558515498e-06,
455
+ "loss": 0.1916,
456
+ "step": 13500
457
+ },
458
+ {
459
+ "epoch": 27.33,
460
+ "eval_accuracy": 0.9283819628647215,
461
+ "eval_f1": 0.9559474626706007,
462
+ "eval_loss": 0.3977676033973694,
463
+ "eval_precision": 0.9875814057989544,
464
+ "eval_runtime": 205.5092,
465
+ "eval_samples_per_second": 12.841,
466
+ "eval_steps_per_second": 1.071,
467
+ "step": 13500
468
+ },
469
+ {
470
+ "epoch": 28.34,
471
+ "learning_rate": 3.8124692486117947e-06,
472
+ "loss": 0.1849,
473
+ "step": 14000
474
+ },
475
+ {
476
+ "epoch": 28.34,
477
+ "eval_accuracy": 0.9215611974232664,
478
+ "eval_f1": 0.9506673563440831,
479
+ "eval_loss": 0.4528682827949524,
480
+ "eval_precision": 0.9865112585967588,
481
+ "eval_runtime": 212.4387,
482
+ "eval_samples_per_second": 12.422,
483
+ "eval_steps_per_second": 1.036,
484
+ "step": 14000
485
+ },
486
+ {
487
+ "epoch": 29.35,
488
+ "learning_rate": 2.7581359387080904e-06,
489
+ "loss": 0.1844,
490
+ "step": 14500
491
+ },
492
+ {
493
+ "epoch": 29.35,
494
+ "eval_accuracy": 0.9314134141720348,
495
+ "eval_f1": 0.9566213429287339,
496
+ "eval_loss": 0.3853737413883209,
497
+ "eval_precision": 0.9863541882706378,
498
+ "eval_runtime": 205.8351,
499
+ "eval_samples_per_second": 12.821,
500
+ "eval_steps_per_second": 1.069,
501
+ "step": 14500
502
+ },
503
+ {
504
+ "epoch": 30.36,
505
+ "learning_rate": 1.7038026288043862e-06,
506
+ "loss": 0.1831,
507
+ "step": 15000
508
+ },
509
+ {
510
+ "epoch": 30.36,
511
+ "eval_accuracy": 0.9257294429708223,
512
+ "eval_f1": 0.9527879636596958,
513
+ "eval_loss": 0.41776272654533386,
514
+ "eval_precision": 0.9853006909522924,
515
+ "eval_runtime": 210.65,
516
+ "eval_samples_per_second": 12.528,
517
+ "eval_steps_per_second": 1.044,
518
+ "step": 15000
519
+ },
520
+ {
521
+ "epoch": 31.38,
522
+ "learning_rate": 6.494693189006819e-07,
523
+ "loss": 0.1778,
524
+ "step": 15500
525
+ },
526
+ {
527
+ "epoch": 31.38,
528
+ "eval_accuracy": 0.9359605911330049,
529
+ "eval_f1": 0.9606362253618668,
530
+ "eval_loss": 0.37370702624320984,
531
+ "eval_precision": 0.9883638648463977,
532
+ "eval_runtime": 211.0911,
533
+ "eval_samples_per_second": 12.502,
534
+ "eval_steps_per_second": 1.042,
535
+ "step": 15500
536
+ },
537
+ {
538
+ "epoch": 32.0,
539
+ "step": 15808,
540
+ "total_flos": 1.2696857331997786e+20,
541
+ "train_loss": 0.858633176759187,
542
+ "train_runtime": 80385.1912,
543
+ "train_samples_per_second": 9.454,
544
+ "train_steps_per_second": 0.197
545
+ }
546
+ ],
547
+ "max_steps": 15808,
548
+ "num_train_epochs": 32,
549
+ "total_flos": 1.2696857331997786e+20,
550
+ "trial_name": null,
551
+ "trial_params": null
552
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0d3e78ce7e6b5357e48fd160a2174336ba6ca6dd12d39d163281dca96d3ddbde
3
+ size 3503