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Whisper Base ML - Bharat Ramanathan
This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2456
- Wer: 48.0535
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: 64
- eval_batch_size: 32
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7249 | 4.02 | 500 | 0.3786 | 70.8029 |
| 0.3377 | 4.02 | 1000 | 0.2477 | 56.2044 |
| 0.25 | 9.01 | 1500 | 0.2241 | 49.5134 |
| 0.2009 | 14.01 | 2000 | 0.2158 | 46.9586 |
| 0.1674 | 19.0 | 2500 | 0.2188 | 49.3917 |
| 0.142 | 23.02 | 3000 | 0.2194 | 49.6350 |
| 0.123 | 28.01 | 3500 | 0.2280 | 49.7567 |
| 0.1103 | 33.01 | 4000 | 0.2424 | 51.4599 |
| 0.0999 | 38.0 | 4500 | 0.2435 | 50.6083 |
| 0.0951 | 42.02 | 5000 | 0.2456 | 48.0535 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
