wr_md
This model is a fine-tuned version of openai/whisper-base on the wr_ds dataset. It achieves the following results on the evaluation set:
- Loss: 0.4690
- Cer: 32.7677
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: 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: 500
- training_steps: 2600
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.7558 | 3.8462 | 1000 | 1.0555 | 65.3794 |
| 0.0785 | 7.6923 | 2000 | 0.4690 | 32.7677 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.0
- Datasets 3.0.2
- Tokenizers 0.20.1
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Base model
openai/whisper-base