---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
- bleu
model-index:
- name: whisper-small-GL-EN
  results: []
datasets:
- juanjucm/FLEURS-SpeechT-GL-EN
- juanjucm/OpenHQ-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-small-GL-EN

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on [juanjucm/FLEURS-SpeechT-GL-EN](https://huggingface.co/datasets/juanjucm/FLEURS-SpeechT-GL-EN).
The training dataset has been augmented using train split from [juanjucm/OpenHQ-SpeechT-GL-EN](https://huggingface.co/datasets/juanjucm/OpenHQ-SpeechT-GL-EN)

It achieves the following results on the evaluation set (evaluated only on [juanjucm/FLEURS-SpeechT-GL-EN](https://huggingface.co/datasets/juanjucm/FLEURS-SpeechT-GL-EN)):
- Loss: 1.6335
- Wer: 67.2612
- Bleu: 22.2158

## 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: 1.25e-05
- 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: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Bleu    |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.6816        | 1.0   | 236  | 1.6335          | 67.2612 | 22.2158 |
| 0.1904        | 2.0   | 472  | 1.7234          | 69.9647 | 21.0583 |
| 0.2177        | 3.0   | 708  | 1.8764          | 73.2720 | 19.0086 |
| 0.0334        | 4.0   | 944  | 2.0541          | 72.6774 | 19.7679 |
| 0.0129        | 5.0   | 1180 | 2.1722          | 70.6708 | 19.8076 |
| 0.011         | 6.0   | 1416 | 2.2637          | 71.2653 | 19.7416 |
| 0.0062        | 7.0   | 1652 | 2.3214          | 70.3920 | 20.3474 |
| 0.0067        | 8.0   | 1888 | 2.3405          | 71.9621 | 20.1999 |


### Framework versions

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