whisper-medium-swagen-baseline-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: 0.5467
- Wer: 0.3207
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
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
2.7024 | 0.4759 | 200 | 0.8279 | 0.4665 |
1.869 | 0.9518 | 400 | 0.6452 | 0.4121 |
1.312 | 1.4259 | 600 | 0.6094 | 0.5347 |
1.2453 | 1.9018 | 800 | 0.5467 | 0.3207 |
0.479 | 2.3760 | 1000 | 0.5666 | 0.3466 |
0.4764 | 2.8519 | 1200 | 0.5479 | 0.3031 |
0.1929 | 3.3260 | 1400 | 0.5637 | 0.3558 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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openai/whisper-medium