---
language:
- ga
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- ymoslem/IWSLT2023-GA-EN
- ymoslem/FLEURS-GA-EN
- ymoslem/BitesizeIrish-GA-EN
- ymoslem/SpokenWords-GA-EN-MTed
- ymoslem/Tatoeba-Speech-Irish
- ymoslem/Wikimedia-Speech-Irish
metrics:
- bleu
- wer
model-index:
- name: Whisper Small GA-EN Speech Translation
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia
      type: ymoslem/IWSLT2023-GA-EN
    metrics:
    - name: Bleu
      type: bleu
      value: 23.1
    - name: Wer
      type: wer
      value: 82.89058982440342
---

<!-- 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 GA-EN Speech Translation

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2172
- Bleu: 23.1
- Chrf: 42.54
- Wer: 82.8906

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.03
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu  | Chrf  | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:-----:|:-----:|:--------:|
| 2.8459        | 0.07  | 100  | 2.0769          | 3.28  | 18.43 | 149.0770 |
| 2.3328        | 0.13  | 200  | 1.8396          | 4.5   | 22.06 | 207.7443 |
| 2.1669        | 0.2   | 300  | 1.6215          | 14.6  | 30.8  | 89.1941  |
| 1.8606        | 0.26  | 400  | 1.5030          | 14.65 | 33.33 | 92.4358  |
| 1.7255        | 0.33  | 500  | 1.4085          | 14.9  | 35.14 | 103.8271 |
| 1.5855        | 0.39  | 600  | 1.3587          | 15.78 | 35.02 | 103.0617 |
| 1.5875        | 0.46  | 700  | 1.2986          | 25.3  | 41.37 | 69.4732  |
| 1.44          | 0.53  | 800  | 1.2575          | 25.78 | 42.23 | 70.0585  |
| 1.3317        | 0.59  | 900  | 1.2338          | 23.24 | 41.64 | 79.1085  |
| 1.3166        | 0.66  | 1000 | 1.2172          | 23.1  | 42.54 | 82.8906  |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2