Whisper Small Hi gpu
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 2.8500
- Wer: 194.9420
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: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 8.6847 | 2.44 | 500 | 8.6186 | 184.5213 |
| 7.0074 | 4.88 | 1000 | 6.9394 | 502.2010 |
| 5.0316 | 7.32 | 1500 | 4.9749 | 693.9939 |
| 3.7844 | 9.76 | 2000 | 3.7445 | 447.2488 |
| 3.2504 | 12.2 | 2500 | 3.2245 | 326.1619 |
| 3.0134 | 14.63 | 3000 | 2.9979 | 217.9463 |
| 2.8995 | 17.07 | 3500 | 2.8893 | 213.6164 |
| 2.8678 | 19.51 | 4000 | 2.8500 | 194.9420 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+rocm5.4.2
- Datasets 2.14.5
- Tokenizers 0.12.1
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Base model
openai/whisper-small