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whisper-large-v3-peft
This model is a fine-tuned version of openai/whisper-large-v3 on the CFN Proposal Audio dataset. It achieves the following results on the evaluation set:
- Loss: 0.2785
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 |
---|---|---|---|
0.3111 | 1.0 | 191 | 0.3036 |
0.1985 | 2.0 | 382 | 0.2830 |
0.1435 | 3.0 | 573 | 0.2785 |
Framework versions
- PEFT 0.12.1.dev0
- Transformers 4.43.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for shray98/temp
Base model
openai/whisper-large-v3