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STT_Model_17
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1172
- Wer: 0.1190
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.1934 | 2.1 | 500 | 3.7998 | 0.9999 |
| 1.14 | 4.2 | 1000 | 0.4083 | 0.3740 |
| 0.2217 | 6.3 | 1500 | 0.2515 | 0.2184 |
| 0.1276 | 8.4 | 2000 | 0.1623 | 0.1803 |
| 0.0914 | 10.5 | 2500 | 0.1586 | 0.1672 |
| 0.0731 | 12.61 | 3000 | 0.1648 | 0.1583 |
| 0.0572 | 14.71 | 3500 | 0.4059 | 0.1534 |
| 0.054 | 16.81 | 4000 | 0.1694 | 0.1391 |
| 0.043 | 18.91 | 4500 | 0.1390 | 0.1439 |
| 0.035 | 21.01 | 5000 | 0.1210 | 0.1362 |
| 0.0317 | 23.11 | 5500 | 0.1389 | 0.1285 |
| 0.031 | 25.21 | 6000 | 0.1340 | 0.1316 |
| 0.0266 | 27.31 | 6500 | 0.1312 | 0.1280 |
| 0.0209 | 29.41 | 7000 | 0.1484 | 0.1256 |
| 0.0184 | 31.51 | 7500 | 0.1345 | 0.1289 |
| 0.0201 | 33.61 | 8000 | 0.1350 | 0.1248 |
| 0.026 | 35.71 | 8500 | 0.1226 | 0.1235 |
| 0.016 | 37.82 | 9000 | 0.1235 | 0.1232 |
| 0.0115 | 39.92 | 9500 | 0.1223 | 0.1216 |
| 0.013 | 42.02 | 10000 | 0.1314 | 0.1206 |
| 0.0225 | 44.12 | 10500 | 0.1158 | 0.1211 |
| 0.011 | 46.22 | 11000 | 0.1181 | 0.1203 |
| 0.0106 | 48.32 | 11500 | 0.1172 | 0.1190 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
