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libri-alpha-1-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: 53.0700
- Wer: 0.1137
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 |
---|---|---|---|---|
406.6609 | 0.75 | 100 | 92.6621 | 0.1514 |
332.8654 | 1.49 | 200 | 75.1632 | 0.1429 |
300.7975 | 2.24 | 300 | 69.9229 | 0.1413 |
288.1078 | 2.99 | 400 | 66.7404 | 0.1361 |
262.5671 | 3.73 | 500 | 60.1363 | 0.1314 |
246.594 | 4.48 | 600 | 59.8725 | 0.1289 |
232.3433 | 5.22 | 700 | 59.7349 | 0.1274 |
232.5868 | 5.97 | 800 | 58.1594 | 0.1266 |
225.2652 | 6.72 | 900 | 57.0715 | 0.1248 |
222.3506 | 7.46 | 1000 | 56.8740 | 0.1253 |
210.8775 | 8.21 | 1100 | 55.6375 | 0.1235 |
210.2934 | 8.96 | 1200 | 54.7285 | 0.1223 |
212.0601 | 9.7 | 1300 | 54.6263 | 0.1224 |
203.2785 | 10.45 | 1400 | 54.7651 | 0.1241 |
200.5735 | 11.19 | 1500 | 54.7737 | 0.1238 |
199.7971 | 11.94 | 1600 | 54.7460 | 0.1214 |
198.5452 | 12.69 | 1700 | 54.5335 | 0.1222 |
192.6993 | 13.43 | 1800 | 54.3382 | 0.1209 |
195.9604 | 14.18 | 1900 | 54.0138 | 0.1188 |
190.6209 | 14.93 | 2000 | 55.2720 | 0.1219 |
197.205 | 15.67 | 2100 | 54.4430 | 0.1193 |
182.2428 | 16.42 | 2200 | 53.7938 | 0.1195 |
183.4877 | 17.16 | 2300 | 53.0349 | 0.1151 |
178.3634 | 17.91 | 2400 | 53.0706 | 0.1157 |
184.3548 | 18.66 | 2500 | 53.0254 | 0.1158 |
184.6175 | 19.4 | 2600 | 53.2929 | 0.1159 |
190.0462 | 20.15 | 2700 | 52.8959 | 0.1157 |
179.8124 | 20.9 | 2800 | 53.0652 | 0.1147 |
178.4741 | 21.64 | 2900 | 53.5907 | 0.1155 |
175.1646 | 22.39 | 3000 | 53.5027 | 0.1155 |
172.7706 | 23.13 | 3100 | 53.3478 | 0.1146 |
182.5294 | 23.88 | 3200 | 53.2863 | 0.1152 |
183.6617 | 24.63 | 3300 | 53.3587 | 0.1146 |
180.0207 | 25.37 | 3400 | 53.2285 | 0.1140 |
180.7319 | 26.12 | 3500 | 53.1544 | 0.1140 |
171.5148 | 26.87 | 3600 | 53.0734 | 0.1144 |
177.4159 | 27.61 | 3700 | 53.1536 | 0.1138 |
168.6823 | 28.36 | 3800 | 53.1117 | 0.1138 |
176.7611 | 29.1 | 3900 | 53.0962 | 0.1135 |
176.1258 | 29.85 | 4000 | 53.0700 | 0.1137 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.11.0