Whisper Small Hi - Sanchit Gandhi
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4049
- Wer: 35.7784
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: 200
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2505 | 1.9417 | 200 | 0.3317 | 40.8406 |
| 0.0809 | 3.8835 | 400 | 0.3037 | 36.1339 |
| 0.0255 | 5.8252 | 600 | 0.3527 | 35.6683 |
| 0.0078 | 7.7670 | 800 | 0.3872 | 35.5202 |
| 0.004 | 9.7087 | 1000 | 0.4049 | 35.7784 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small