---
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: 30.93
    - name: Wer
      type: wer
      value: 63.12471859522738
---

<!-- 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: 1.2119
- Bleu: 30.93
- Chrf: 49.09
- Wer: 63.1247

## 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: 0.02
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Bleu  | Chrf  | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:-----:|:-----:|:---------------:|:--------:|
| 2.7017        | 0.02   | 100  | 2.83  | 14.96 | 2.4392          | 169.5182 |
| 2.6732        | 0.04   | 200  | 7.27  | 22.72 | 1.9552          | 103.2868 |
| 2.1622        | 0.07   | 300  | 11.43 | 30.01 | 1.7297          | 108.2395 |
| 2.0314        | 0.09   | 400  | 12.96 | 31.0  | 1.6499          | 106.4385 |
| 1.7219        | 0.11   | 500  | 12.94 | 33.67 | 1.5543          | 107.6092 |
| 1.577         | 0.13   | 600  | 12.84 | 35.03 | 1.4812          | 118.5502 |
| 1.3569        | 0.1532 | 700  | 1.4559| 19.94 | 38.08           | 84.2864  |
| 1.3401        | 0.1751 | 800  | 1.3855| 13.39 | 36.11           | 126.4295 |
| 1.2272        | 0.1970 | 900  | 1.3764| 24.39 | 41.75           | 70.7789  |
| 1.2793        | 0.2189 | 1000 | 1.3389| 23.01 | 42.13           | 80.6844  |
| 1.0383        | 0.2408 | 1100 | 1.3125| 23.42 | 43.59           | 82.3953  |
| 1.0485        | 0.2627 | 1200 | 1.2996| 25.42 | 42.99           | 69.4732  |
| 1.0427        | 0.2846 | 1300 | 1.2996| 29.24 | 45.36           | 65.6461  |
| 0.8174        | 0.3065 | 1400 | 1.2522| 27.28 | 45.67           | 68.3926  |
| 0.7345        | 0.3284 | 1500 | 1.2349| 26.35 | 46.78           | 79.1986  |
| 0.7551        | 0.3503 | 1600 | 1.2317| 27.81 | 46.49           | 70.6439  |
| 0.6765        | 0.3722 | 1700 | 1.2062| 27.62 | 47.46           | 70.9140  |
| 0.6613        | 0.3940 | 1800 | 1.2087| 26.56 | 47.12           | 72.8050  |
| 0.6181        | 0.4159 | 1900 | 1.2139| 29.91 | 48.76           | 65.2859  |
| 0.5809        | 0.4378 | 2000 | 1.2119| 30.93 | 49.09           | 63.1247  |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1