whisper-medium-swagen-combined-5hrs-model
This model is a fine-tuned version of openai/whisper-medium on the swagen dataset. It achieves the following results on the evaluation set:
- Loss: 0.5513
- Wer: 0.3389
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: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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
- num_epochs: 30.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
2.4783 | 0.4770 | 200 | 0.8261 | 0.4707 |
1.972 | 0.9541 | 400 | 0.6396 | 0.3808 |
1.2266 | 1.4293 | 600 | 0.5920 | 0.3696 |
1.1413 | 1.9064 | 800 | 0.5513 | 0.3389 |
0.5603 | 2.3816 | 1000 | 0.5737 | 0.3432 |
0.548 | 2.8587 | 1200 | 0.5665 | 0.3043 |
0.2165 | 3.3339 | 1400 | 0.5771 | 0.2967 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
openai/whisper-medium