Whisper Tiny Italian Combine 8k - Chee Li
This model is a fine-tuned version of openai/whisper-tiny on the Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.4500
- Wer: 53.9953
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: 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: 8000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.5398 | 0.0849 | 1000 | 0.6208 | 60.3945 |
0.4876 | 0.1699 | 2000 | 0.5525 | 56.4670 |
0.4505 | 0.2548 | 3000 | 0.5174 | 53.1158 |
0.4178 | 0.3398 | 4000 | 0.4916 | 52.5323 |
0.4058 | 0.4247 | 5000 | 0.4736 | 51.7368 |
0.3871 | 0.5097 | 6000 | 0.4621 | 52.8128 |
0.3736 | 0.5946 | 7000 | 0.4533 | 53.4402 |
0.3844 | 0.6796 | 8000 | 0.4500 | 53.9953 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.20.1
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Base model
openai/whisper-tiny