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openai-whisper-large-v2-LORA-colab
This model is a fine-tuned version of openai/whisper-large-v2 on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1374
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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1865 | 1.0 | 1410 | 0.1704 |
| 0.0955 | 2.0 | 2820 | 0.1426 |
| 0.0165 | 3.0 | 4230 | 0.1374 |
Framework versions
- PEFT 0.8.2
- Transformers 4.39.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.1.dev0
- Tokenizers 0.15.1
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Model tree for dah1214/openai-whisper-large-v2-LORA-colab
Base model
openai/whisper-large-v2