whisper_AN_demo
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: 0.5163
- Wer Ortho: 34.7268
- Wer: 29.6857
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: 16
- eval_batch_size: 16
- 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: 500
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
0.6419 | 0.05 | 100 | 0.8019 | 31.6674 | 26.4281 |
0.2769 | 0.1 | 200 | 0.5559 | 32.3914 | 27.3457 |
0.2674 | 0.15 | 300 | 0.5354 | 39.1172 | 33.8151 |
0.2672 | 0.19 | 400 | 0.5247 | 34.6333 | 29.6628 |
0.2876 | 0.24 | 500 | 0.5163 | 34.7268 | 29.6857 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Base model
openai/whisper-small