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Whisper Medium
This model is a fine-tuned version of openai/whisper-medium on the miosipof/asr_en dataset. It achieves the following results on the evaluation set:
- Loss: 0.3170
- Wer: 20.5788
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: 0.001
- 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: 32
- training_steps: 128
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.8843 | 1.0847 | 32 | 0.8819 | 135.0482 |
| 0.3624 | 2.1695 | 64 | 0.3312 | 47.1061 |
| 0.1637 | 3.2542 | 96 | 0.3231 | 22.1865 |
| 0.0903 | 4.3390 | 128 | 0.3170 | 20.5788 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Model tree for miosipof/asr_EN_medium_v1
Base model
openai/whisper-medium