Whisper Small Mar - Harpreet Singh Anand
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: 0.1644
- Wer: 14.3917
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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0018 | 12.66 | 1000 | 0.1550 | 16.6181 |
| 0.0001 | 25.32 | 2000 | 0.1529 | 14.6303 |
| 0.0 | 37.97 | 3000 | 0.1617 | 14.4977 |
| 0.0 | 50.63 | 4000 | 0.1644 | 14.3917 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.1.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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