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STT_Model_4
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: 0.2311
- Wer: 0.1373
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: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.4196 | 5.68 | 500 | 0.9866 | 0.6983 |
| 0.3696 | 11.36 | 1000 | 0.8788 | 0.4010 |
| 0.1182 | 17.05 | 1500 | 0.2187 | 0.1947 |
| 0.0658 | 22.73 | 2000 | 0.2578 | 0.1757 |
| 0.0421 | 28.41 | 2500 | 0.2178 | 0.1609 |
| 0.0346 | 34.09 | 3000 | 0.2038 | 0.1584 |
| 0.0285 | 39.77 | 3500 | 0.2187 | 0.1594 |
| 0.0228 | 45.45 | 4000 | 0.2114 | 0.1445 |
| 0.0262 | 51.14 | 4500 | 0.2201 | 0.1631 |
| 0.0162 | 56.82 | 5000 | 0.2078 | 0.1424 |
| 0.0135 | 62.5 | 5500 | 0.1989 | 0.1393 |
| 0.0128 | 68.18 | 6000 | 0.2118 | 0.1410 |
| 0.0104 | 73.86 | 6500 | 0.2158 | 0.1361 |
| 0.0081 | 79.55 | 7000 | 0.2154 | 0.1348 |
| 0.0067 | 85.23 | 7500 | 0.2107 | 0.1358 |
| 0.0067 | 90.91 | 8000 | 0.2161 | 0.1373 |
| 0.0056 | 96.59 | 8500 | 0.2311 | 0.1373 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
