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Whisper-Small-TF-TIMIT-FLEUR
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8885
- Wer: 35.0461
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: 6.25e-06
- train_batch_size: 16
- eval_batch_size: 8
- 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: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4965 | 1.27 | 500 | 0.9304 | 37.3857 |
| 0.1668 | 2.54 | 1000 | 0.8561 | 32.7384 |
| 0.069 | 3.81 | 1500 | 0.8093 | 52.7441 |
| 0.0152 | 5.08 | 2000 | 0.9021 | 54.9437 |
| 0.0083 | 6.35 | 2500 | 0.8471 | 57.3611 |
| 0.0021 | 7.61 | 3000 | 0.8885 | 35.0461 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2
