Whisper Small Hi - Vyapar
This model is a fine-tuned version of openai/whisper-small on the Vyapar Calling Data dataset. It achieves the following results on the evaluation set:
- Loss: 2.0664
- Wer: 62.9259
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|---|---|---|---|---|
| 0.1183 | 8.7753 | 1000 | 1.5163 | 56.7134 |
| 0.0037 | 17.5463 | 2000 | 1.8823 | 54.8297 |
| 0.0003 | 26.3172 | 3000 | 2.0341 | 54.9499 |
| 0.0002 | 35.0881 | 4000 | 2.0664 | 62.9259 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
openai/whisper-small