---
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-FLEURS-GL-EN
  results: []
datasets:
- juanjucm/FLEURS-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-FLEURS-GL-EN

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4958
- Wer: 71.6814
- Bleu: 18.9665

## 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: 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
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      | Bleu    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|
| 4.2751        | 1.0   | 5    | 3.8850          | 76.6962  | 18.0512 |
| 2.3984        | 2.0   | 10   | 2.6965          | 97.0501  | 13.5327 |
| 1.4958        | 3.0   | 15   | 2.2308          | 71.6814  | 18.9665 |
| 1.27          | 4.0   | 20   | 2.0454          | 128.3186 | 12.2446 |


### Framework versions

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