metadata
library_name: transformers
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
metrics:
- wer
- bleu
model-index:
- name: whisper-large-v3-turbo-OpenSLR-GL
results: []
datasets:
- juanjucm/OpenSLR-SpeechT-GL-EN
language:
- gl
whisper-large-v3-turbo-OpenSLR-GL
This model is a fine-tuned version of openai/whisper-large-v3-turbo on juanjucm/OpenSLR-SpeechT-GL-EN. It achieves the following results on the evaluation set:
- Loss: 0.1613
- Wer: 10.6845
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2739 | 1.0 | 75 | 0.1898 | 11.4023 |
| 0.1841 | 2.0 | 150 | 0.1819 | 10.3673 |
| 0.0542 | 3.0 | 225 | 0.1919 | 10.6177 |
| 0.0399 | 4.0 | 300 | 0.1934 | 11.1352 |
| 0.0264 | 5.0 | 375 | 0.2042 | 11.2688 |
| 0.0143 | 6.0 | 450 | 0.2075 | 10.3840 |
| 0.0056 | 7.0 | 525 | 0.2198 | 10.8347 |
| 0.0063 | 8.0 | 600 | 0.2217 | 10.9683 |
| 0.0037 | 9.0 | 675 | 0.2258 | 10.5509 |
| 0.0042 | 10.0 | 750 | 0.2278 | 10.6845 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0