names-whisper-en-spectrogram-pitch-shifted
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: 0.2384
- Ner percent: 101.9340
- Wer: 5.3520
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: 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Ner percent | Wer |
|---|---|---|---|---|---|
| 0.036 | 5.0251 | 1000 | 0.2288 | 99.9682 | 6.2317 |
| 0.0013 | 10.0503 | 2000 | 0.2292 | 97.7273 | 5.6542 |
| 0.0005 | 15.0754 | 3000 | 0.2334 | 102.4688 | 5.3084 |
| 0.0003 | 20.1005 | 4000 | 0.2368 | 101.9340 | 5.3621 |
| 0.0003 | 25.1256 | 5000 | 0.2384 | 101.9340 | 5.3520 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small