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whisper-medium-cdsd1h-lora
This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8196
- Wer: 68.7556
- Cer: 42.4589
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.8709 | 1.0 | 559 | 0.9190 | 78.1558 | 48.5899 |
| 0.6026 | 2.0 | 1118 | 0.8174 | 73.1871 | 45.7778 |
| 0.3343 | 3.0 | 1677 | 0.7864 | 70.3223 | 41.8295 |
| 0.1663 | 4.0 | 2236 | 0.7846 | 68.8004 | 44.3636 |
| 0.0664 | 5.0 | 2795 | 0.8196 | 68.7556 | 42.4589 |
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.0.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for llillillil/whisper-medium-cdsd1h-lora
Base model
openai/whisper-medium