Whisper Small Hi - Sanchit Gandhi
This model is a fine-tuned version of openai/whisper-small on the AfriVoice dataset. It achieves the following results on the evaluation set:
- Loss: 1.6526
- Wer: 53.5292
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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.0002 | 153.8462 | 1000 | 1.4799 | 52.3072 |
| 0.0001 | 307.6923 | 2000 | 1.5528 | 52.1298 |
| 0.0 | 461.5385 | 3000 | 1.6058 | 52.3033 |
| 0.0 | 615.3846 | 4000 | 1.6294 | 52.8546 |
| 0.0 | 769.2308 | 5000 | 1.6526 | 53.5292 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.1.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small