whisper-tiny-transcription
This model is a fine-tuned version of openai/whisper-tiny on the covost2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6300
- Wer: 90.7309
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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 6000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.4768 | 1.3407 | 1000 | 0.6468 | 92.3030 |
0.3982 | 2.6814 | 2000 | 0.6164 | 90.8942 |
0.2697 | 4.0215 | 3000 | 0.6099 | 90.2613 |
0.2219 | 5.3622 | 4000 | 0.6209 | 90.2409 |
0.1836 | 6.7029 | 5000 | 0.6272 | 90.5063 |
0.1622 | 8.0429 | 6000 | 0.6300 | 90.7309 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
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Base model
openai/whisper-tiny