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timit-supervised
This model is a fine-tuned version of Experiments/single_dataset/timit-supervised/checkpoint-3500 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1272
- Wer: 0.0532
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: 16
- 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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0554 | 1.77 | 500 | 0.1310 | 0.0697 |
| 0.0509 | 3.53 | 1000 | 0.1497 | 0.0710 |
| 0.038 | 5.3 | 1500 | 0.1190 | 0.0659 |
| 0.0328 | 7.07 | 2000 | 0.0926 | 0.0596 |
| 0.0247 | 8.83 | 2500 | 0.0873 | 0.0570 |
| 0.0229 | 10.6 | 3000 | 0.0890 | 0.0532 |
| 0.0183 | 12.37 | 3500 | 0.0969 | 0.0532 |
| 0.0326 | 14.13 | 4000 | 0.0809 | 0.0469 |
| 0.03 | 15.9 | 4500 | 0.0758 | 0.0444 |
| 0.0264 | 17.67 | 5000 | 0.0973 | 0.0520 |
| 0.0244 | 19.43 | 5500 | 0.1272 | 0.0532 |
Framework versions
- Transformers 4.14.1
- Pytorch 1.10.2
- Datasets 1.18.2
- Tokenizers 0.10.3
