ft_model
This model is a fine-tuned version of openai/whisper-base on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.6109
- Cer: 16.9926
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: 1
- eval_batch_size: 1
- 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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.3246 | 0.25 | 500 | 0.6696 | 18.6400 |
| 0.3243 | 0.5 | 1000 | 0.6509 | 18.5784 |
| 0.2622 | 0.75 | 1500 | 0.6245 | 17.5366 |
| 0.3307 | 1.0 | 2000 | 0.6109 | 16.9926 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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