Whisper Small Or- Mudit Sharma
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3656
- Wer: 52.4265
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0192 | 7.8125 | 1000 | 0.2476 | 56.1209 |
| 0.0011 | 15.625 | 2000 | 0.2956 | 52.8128 |
| 0.0001 | 23.4375 | 3000 | 0.3320 | 52.6616 |
| 0.0 | 31.25 | 4000 | 0.3582 | 52.6280 |
| 0.0 | 39.0625 | 5000 | 0.3656 | 52.4265 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small