whisper-small-ablation-updated-baseline
This model is a fine-tuned version of openai/whisper-small on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.4145
- Wer: 17.4631
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4147 | 0.8157 | 500 | 0.4170 | 18.9381 |
| 0.234 | 1.6313 | 1000 | 0.4145 | 17.4631 |
Framework versions
- Transformers 4.45.0
- Pytorch 2.11.0+cu130
- Datasets 3.0.1
- Tokenizers 0.20.0