metadata
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo-ft-cv-cy-train-all-plus-other-with-excluded
results: []
whisper-large-v3-turbo-ft-cv-cy-train-all-plus-other-with-excluded
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: 0.3134
- Wer: 0.1746
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|---|---|---|---|---|
| 0.2147 | 1.4144 | 1000 | 0.3066 | 0.2349 |
| 0.0989 | 2.8289 | 2000 | 0.2775 | 0.2072 |
| 0.0295 | 4.2433 | 3000 | 0.2935 | 0.1919 |
| 0.0109 | 5.6577 | 4000 | 0.3011 | 0.1828 |
| 0.0016 | 7.0721 | 5000 | 0.3134 | 0.1746 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1