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em_wav
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6818
- Wer: 96.8954
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: 1e-05
- 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: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.9478 | 0.08 | 100 | 3.4707 | 99.1013 |
| 2.5514 | 0.16 | 200 | 2.4346 | 96.7116 |
| 1.7725 | 0.24 | 300 | 1.7743 | 99.9387 |
| 1.752 | 0.32 | 400 | 1.7586 | 97.1201 |
| 1.7447 | 0.4 | 500 | 1.7461 | 98.1413 |
| 1.7118 | 0.48 | 600 | 1.7304 | 97.1201 |
| 1.6823 | 0.56 | 700 | 1.7147 | 97.1201 |
| 1.7535 | 0.65 | 800 | 1.6987 | 97.8145 |
| 1.6772 | 0.73 | 900 | 1.6895 | 97.7941 |
| 1.6552 | 0.81 | 1000 | 1.6818 | 96.8954 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.1+cu117
- Datasets 2.13.0
- Tokenizers 0.13.3
