Whisper tiny epoch test - Perrie
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4754
- Cer: 57.5895
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 700
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.4064 | 0.99 | 700 | 0.4476 | 33.9306 |
| 0.3595 | 1.99 | 1400 | 0.4218 | 29.0735 |
| 0.2349 | 2.98 | 2100 | 0.4197 | 25.9553 |
| 0.1507 | 3.97 | 2800 | 0.4237 | 25.9104 |
| 0.1003 | 4.96 | 3500 | 0.4309 | 35.9495 |
| 0.0601 | 5.96 | 4200 | 0.4442 | 29.8821 |
| 0.0481 | 6.95 | 4900 | 0.4551 | 36.7132 |
| 0.0296 | 7.94 | 5600 | 0.4640 | 38.9224 |
| 0.0207 | 8.94 | 6300 | 0.4721 | 47.1645 |
| 0.0169 | 9.93 | 7000 | 0.4754 | 57.5895 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 1.12.1
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
openai/whisper-tiny