---
library_name: transformers
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: whisper-large-v3-turbo-gl-en
  results: []
datasets:
- juanjucm/OpenSLR-SpeechT-GL-EN
language:
- gl
- en
---

<!-- 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-gl-en

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 test set:
- Loss: 0.9360
- Bleu: 55.6535

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Bleu    |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.2758        | 1.6667  | 250  | 0.7646          | 50.6055 |
| 0.0592        | 3.3333  | 500  | 0.7730          | 53.1258 |
| 0.0406        | 5.0     | 750  | 0.7860          | 53.3406 |
| 0.0173        | 6.6667  | 1000 | 0.8358          | 51.9789 |
| 0.0091        | 8.3333  | 1250 | 0.8909          | 54.4806 |
| 0.0071        | 10.0    | 1500 | 0.8862          | 54.2655 |
| 0.0039        | 11.6667 | 1750 | 0.9216          | 52.5119 |
| 0.0014        | 13.3333 | 2000 | 0.9281          | 54.5752 |
| 0.0013        | 15.0    | 2250 | 0.9471          | 54.5791 |
| 0.0009        | 16.6667 | 2500 | 0.9541          | 54.8725 |
| 0.0006        | 18.3333 | 2750 | 0.9614          | 53.1879 |
| 0.0006        | 20.0    | 3000 | 0.9701          | 54.6499 |
| 0.0006        | 21.6667 | 3250 | 0.9739          | 54.4341 |
| 0.0006        | 23.3333 | 3500 | 0.9747          | 54.5311 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0