---
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: 25.68
    - name: Wer
      type: wer
      value: 71.04907699234579
---

<!-- 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: 1.1571
- Bleu: 25.68
- Chrf: 45.53
- Wer: 71.0491

## 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      |
|:-------------:|:-----:|:----:|:---------------:|:-----:|:-----:|:--------:|
| 2.6685        | 0.07  | 100  | 2.0544          | 5.05  | 20.18 | 139.8919 |
| 2.4028        | 0.13  | 200  | 1.7367          | 12.29 | 29.72 | 95.5425  |
| 2.1231        | 0.2   | 300  | 1.6141          | 14.33 | 30.77 | 101.3958 |
| 1.9192        | 0.26  | 400  | 1.4778          | 16.86 | 35.65 | 91.0851  |
| 1.7129        | 0.33  | 500  | 1.3811          | 16.77 | 37.53 | 93.8766  |
| 1.5398        | 0.39  | 600  | 1.3427          | 18.85 | 39.0  | 90.2296  |
| 1.4257        | 0.46  | 700  | 1.2784          | 25.73 | 43.3  | 70.3287  |
| 1.3044        | 0.53  | 800  | 1.2274          | 25.43 | 44.33 | 72.3548  |
| 1.2626        | 0.59  | 900  | 1.1875          | 25.09 | 44.62 | 72.6249  |
| 1.2801        | 0.66  | 1000 | 1.1571          | 25.68 | 45.53 | 71.0491  |


### Framework versions

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