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libri-alpha-0.75-Temp-1-mse
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 40.9574
- Wer: 0.1140
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
314.2983 | 0.75 | 100 | 73.1996 | 0.1509 |
254.3135 | 1.49 | 200 | 61.7104 | 0.1436 |
238.1834 | 2.24 | 300 | 53.4787 | 0.1426 |
212.833 | 2.99 | 400 | 51.2417 | 0.1390 |
202.8803 | 3.73 | 500 | 48.4136 | 0.1323 |
191.6817 | 4.48 | 600 | 45.9843 | 0.1288 |
178.3099 | 5.22 | 700 | 44.9262 | 0.1264 |
176.7728 | 5.97 | 800 | 44.0379 | 0.1287 |
176.0927 | 6.72 | 900 | 43.9972 | 0.1251 |
175.7854 | 7.46 | 1000 | 43.3336 | 0.1253 |
170.2058 | 8.21 | 1100 | 44.0316 | 0.1285 |
157.8171 | 8.96 | 1200 | 42.9391 | 0.1246 |
158.1243 | 9.7 | 1300 | 41.9089 | 0.1216 |
160.1174 | 10.45 | 1400 | 41.7764 | 0.1212 |
157.8857 | 11.19 | 1500 | 41.7168 | 0.1199 |
155.323 | 11.94 | 1600 | 41.5339 | 0.1205 |
149.4838 | 12.69 | 1700 | 41.1427 | 0.1189 |
148.4661 | 13.43 | 1800 | 41.1901 | 0.1181 |
147.2941 | 14.18 | 1900 | 41.1430 | 0.1184 |
151.4415 | 14.93 | 2000 | 41.1998 | 0.1188 |
142.9946 | 15.67 | 2100 | 41.3427 | 0.1180 |
143.8573 | 16.42 | 2200 | 40.9182 | 0.1167 |
144.2671 | 17.16 | 2300 | 41.0134 | 0.1158 |
145.2445 | 17.91 | 2400 | 40.8738 | 0.1170 |
148.3202 | 18.66 | 2500 | 40.6994 | 0.1166 |
138.238 | 19.4 | 2600 | 40.9133 | 0.1173 |
139.9513 | 20.15 | 2700 | 40.8462 | 0.1165 |
142.0799 | 20.9 | 2800 | 40.9641 | 0.1155 |
136.6577 | 21.64 | 2900 | 40.9828 | 0.1162 |
143.027 | 22.39 | 3000 | 41.1197 | 0.1152 |
138.5346 | 23.13 | 3100 | 41.0499 | 0.1153 |
132.8113 | 23.88 | 3200 | 41.1406 | 0.1155 |
136.3161 | 24.63 | 3300 | 41.0155 | 0.1147 |
138.4135 | 25.37 | 3400 | 40.8724 | 0.1147 |
132.4531 | 26.12 | 3500 | 40.8390 | 0.1143 |
131.0835 | 26.87 | 3600 | 41.0005 | 0.1143 |
132.015 | 27.61 | 3700 | 40.9447 | 0.1142 |
132.5831 | 28.36 | 3800 | 40.9810 | 0.1142 |
134.858 | 29.1 | 3900 | 40.9652 | 0.1140 |
135.4016 | 29.85 | 4000 | 40.9574 | 0.1140 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.11.0