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LoRA-Frisian-1h
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_6_1 dataset. It achieves the following results on the evaluation set:
- Loss: 1.5372
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: 0.001
- train_batch_size: 8
- 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: 50
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 15 | 3.9123 |
| 4.3581 | 2.0 | 30 | 2.4747 |
| 4.3581 | 3.0 | 45 | 2.1013 |
| 2.0139 | 4.0 | 60 | 1.7239 |
| 0.8458 | 5.0 | 75 | 1.5361 |
| 0.8458 | 6.0 | 90 | 1.5255 |
| 0.2525 | 7.0 | 105 | 1.5009 |
| 0.2525 | 8.0 | 120 | 1.5346 |
| 0.0726 | 9.0 | 135 | 1.5020 |
| 0.0233 | 10.0 | 150 | 1.5250 |
| 0.0233 | 11.0 | 165 | 1.5127 |
| 0.0152 | 12.0 | 180 | 1.5213 |
| 0.0152 | 13.0 | 195 | 1.5306 |
| 0.0104 | 14.0 | 210 | 1.5349 |
| 0.0093 | 15.0 | 225 | 1.5372 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small