whisper-medium-CAENNAIS
This model is a fine-tuned version of openai/whisper-large-v3-turbo on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5740
- Wer: 26.7396
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: 16
- 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
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 1.0 | 56 | 0.7664 | 33.4990 |
| No log | 2.0 | 112 | 0.4936 | 28.0649 |
| No log | 3.0 | 168 | 0.4702 | 23.7906 |
| No log | 4.0 | 224 | 0.4987 | 28.4957 |
| No log | 5.0 | 280 | 0.4999 | 23.7575 |
| No log | 6.0 | 336 | 0.5567 | 25.3810 |
| No log | 7.0 | 392 | 0.5685 | 23.4924 |
| No log | 8.0 | 448 | 0.5738 | 25.0497 |
| 0.3662 | 9.0 | 504 | 0.6081 | 24.6852 |
| 0.3662 | 10.0 | 560 | 0.5740 | 26.7396 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.0
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Model tree for Rziane/whisper-large-v3-turbo-CAENNAIS
Base model
openai/whisper-large-v3
Finetuned
openai/whisper-large-v3-turbo