Whisper Small Custom - Mattia Colbertaldo
This model is a fine-tuned version of openai/whisper-small on the Mattia's Dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.8726
- Wer: 0.0
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- training_steps: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.1417 | 10.0 | 10 | 3.0808 | 0.0 |
| 0.6544 | 20.0 | 20 | 1.2364 | 57.1429 |
| 0.4179 | 30.0 | 30 | 1.0541 | 57.1429 |
| 0.3622 | 40.0 | 40 | 0.9383 | 1000.0 |
| 0.3339 | 50.0 | 50 | 0.8726 | 0.0 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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