---
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
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# whisper-large-v3-turbo-OpenSLR-GL

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on [juanjucm/OpenSLR-SpeechT-GL-EN](https://huggingface.co/datasets/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