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amk-whisper-v5.5
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8049
- Wer: 28.0612
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: 5e-06
- 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: 2
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.2935 | 1.0 | 1 | 1.0842 | 38.2653 |
| 1.2935 | 2.0 | 2 | 1.0339 | 35.7143 |
| 1.1811 | 3.0 | 3 | 0.9826 | 33.1633 |
| 0.9953 | 4.0 | 4 | 0.9103 | 28.5714 |
| 0.7994 | 5.0 | 5 | 0.8852 | 28.0612 |
| 0.7257 | 6.0 | 6 | 0.8624 | 28.5714 |
| 0.656 | 7.0 | 7 | 0.8423 | 28.8265 |
| 0.5976 | 8.0 | 8 | 0.8274 | 28.5714 |
| 0.5572 | 9.0 | 9 | 0.8110 | 27.8061 |
| 0.5096 | 10.0 | 10 | 0.8049 | 28.0612 |
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
