whisper-medium-ar-tiny
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0900
- Wer: 36.7470
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.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: 10
- training_steps: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.3745 | 2.2222 | 20 | 1.4938 | 56.6265 |
| 1.1549 | 4.4444 | 40 | 1.2452 | 57.2289 |
| 1.0416 | 6.6667 | 60 | 1.1509 | 38.5542 |
| 0.9904 | 8.8889 | 80 | 1.1050 | 38.5542 |
| 0.9493 | 11.1111 | 100 | 1.0900 | 36.7470 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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openai/whisper-medium