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whisper-large-v2-ft-cv16-1__car350_tms-good-30-250504-v1
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1000
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.0498 | 1.0 | 177 | 1.2594 |
| 0.3113 | 2.0 | 354 | 0.1046 |
| 0.1107 | 3.0 | 531 | 0.0912 |
| 0.0852 | 4.0 | 708 | 0.0880 |
| 0.0688 | 5.0 | 885 | 0.0886 |
| 0.0563 | 6.0 | 1062 | 0.0911 |
| 0.0469 | 7.0 | 1239 | 0.0928 |
| 0.0397 | 8.0 | 1416 | 0.0955 |
| 0.0341 | 9.0 | 1593 | 0.0982 |
| 0.0304 | 10.0 | 1770 | 0.1000 |
Framework versions
- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.5.0+cu124
- Datasets 2.21.0
- Tokenizers 0.20.0
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Base model
openai/whisper-large-v2