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whisper-small-finetuned-multilingual-on-kaggle
This model is a fine-tuned version of openai/whisper-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6732
- Wer: 191.2033
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0 | 0 | 2.0460 | 162.1874 |
| 0.3398 | 2.2523 | 1000 | 1.8079 | 181.3942 |
| 0.3015 | 4.5045 | 2000 | 1.7287 | 176.3787 |
| 0.2972 | 6.7568 | 3000 | 1.6952 | 184.4728 |
| 0.2783 | 9.0090 | 4000 | 1.6783 | 183.3356 |
| 0.2877 | 11.2613 | 5000 | 1.6732 | 191.2033 |
Framework versions
- PEFT 0.17.1
- Transformers 4.56.1
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.22.0
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Model tree for fine2006/whisper-small-finetuned-multilingual-on-kaggle
Base model
openai/whisper-base