whisper-small-hi-2
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2909
- Wer: 7.6142
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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1271 | 2.63 | 100 | 0.2529 | 7.3604 |
0.0246 | 5.26 | 200 | 0.2495 | 8.6294 |
0.0087 | 7.89 | 300 | 0.2712 | 8.8832 |
0.0011 | 10.53 | 400 | 0.2693 | 8.8832 |
0.0002 | 13.16 | 500 | 0.2760 | 8.6294 |
0.0002 | 15.79 | 600 | 0.2853 | 7.8680 |
0.0001 | 18.42 | 700 | 0.2866 | 7.6142 |
0.0001 | 21.05 | 800 | 0.2889 | 7.6142 |
0.0001 | 23.68 | 900 | 0.2904 | 7.6142 |
0.0001 | 26.32 | 1000 | 0.2909 | 7.6142 |
Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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