whisper-small-finetuned-minds-14
This model is a fine-tuned version of openai/whisper-small on the MInDS-14 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6328
- Wer Ortho: 0.8836
- Wer: 0.9779
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0017 | 4.48 | 1000 | 0.6328 | 0.8836 | 0.9779 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.0
- Tokenizers 0.13.3
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Base model
openai/whisper-small