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LoRA-Frisian-10m
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: 1.4867
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: 20
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 1.0 | 15 | 2.3256 |
1.8865 | 2.0 | 30 | 2.1013 |
1.8865 | 3.0 | 45 | 1.6160 |
1.0013 | 4.0 | 60 | 1.5231 |
0.292 | 5.0 | 75 | 1.5076 |
0.292 | 6.0 | 90 | 1.4960 |
0.1192 | 7.0 | 105 | 1.4306 |
0.1192 | 8.0 | 120 | 1.4704 |
0.0475 | 9.0 | 135 | 1.4549 |
0.019 | 10.0 | 150 | 1.4525 |
0.019 | 11.0 | 165 | 1.4633 |
0.0074 | 12.0 | 180 | 1.4670 |
0.0074 | 13.0 | 195 | 1.4709 |
0.0048 | 14.0 | 210 | 1.4759 |
0.004 | 15.0 | 225 | 1.4792 |
0.004 | 16.0 | 240 | 1.4820 |
0.0035 | 17.0 | 255 | 1.4841 |
0.0035 | 18.0 | 270 | 1.4855 |
0.0033 | 19.0 | 285 | 1.4862 |
0.0032 | 20.0 | 300 | 1.4867 |
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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Model tree for xuliu15/Frisian_32r_LoRA_10mins
Base model
openai/whisper-small