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---
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: 31.78
- name: Wer
type: wer
value: 62.31427285006754
---
<!-- 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: 1.3732
- Bleu: 31.78
- Chrf: 47.41
- Wer: 62.3143
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 3000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Bleu | Chrf | Validation Loss | Wer |
|:-------------:|:------:|:----:|:-----:|:-----:|:---------------:|:--------:|
| 2.4081 | 0.0438 | 100 | 9.25 | 24.92 | 1.8707 | 101.1706 |
| 1.9316 | 0.0876 | 200 | 13.88 | 32.67 | 1.5419 | 101.5308 |
| 1.5533 | 0.1313 | 300 | 17.52 | 36.68 | 1.4046 | 83.1607 |
| 1.3403 | 0.1751 | 400 | 17.71 | 37.97 | 1.3565 | 93.5615 |
| 1.1303 | 0.2189 | 500 | 19.24 | 40.02 | 1.3224 | 82.0801 |
| 0.9892 | 0.2627 | 600 | 26.07 | 43.16 | 1.3077 | 72.8050 |
| 0.9005 | 0.3065 | 700 | 27.37 | 44.24 | 1.2918 | 64.1603 |
| 0.7547 | 0.3503 | 800 | 27.68 | 44.28 | 1.2754 | 66.0964 |
| 0.7199 | 0.3940 | 900 | 23.99 | 42.99 | 1.2895 | 78.0729 |
| 0.6095 | 0.4378 | 1000 | 1.2716| 16.56 | 41.2 | 116.5691 |
| 0.5072 | 0.4816 | 1100 | 1.2901| 25.39 | 44.04 | 75.2364 |
| 0.4599 | 0.5254 | 1200 | 1.2634| 28.45 | 45.71 | 67.0419 |
| 0.3987 | 0.5692 | 1300 | 1.3004| 25.84 | 45.63 | 75.1013 |
| 0.3443 | 0.6130 | 1400 | 1.2871| 29.09 | 46.25 | 65.4210 |
| 0.2882 | 0.6567 | 1500 | 1.3242| 29.14 | 44.4 | 66.0063 |
| 0.2687 | 0.7005 | 1600 | 1.3135| 22.9 | 43.76 | 92.2557 |
| 0.2059 | 0.7443 | 1700 | 1.3160| 31.13 | 47.45 | 63.6650 |
| 0.1991 | 0.7881 | 1800 | 1.2960| 31.45 | 47.47 | 63.6650 |
| 0.1523 | 0.8319 | 1900 | 1.3215| 31.21 | 47.38 | 64.1153 |
| 0.1349 | 0.8757 | 2000 | 1.3402| 30.58 | 46.32 | 63.7551 |
| 0.111 | 0.9194 | 2100 | 1.3311| 30.92 | 48.17 | 62.2242 |
| 0.1055 | 0.9632 | 2200 | 1.3548| 30.56 | 46.56 | 65.2409 |
| 0.0525 | 1.0070 | 2300 | 1.3754| 31.28 | 48.1 | 64.2954 |
| 0.0498 | 1.0508 | 2400 | 1.3729| 31.16 | 47.8 | 61.7290 |
| 0.0372 | 1.0946 | 2500 | 1.3498| 32.13 | 48.77 | 61.4588 |
| 0.029 | 1.1384 | 2600 | 1.3723| 32.04 | 48.32 | 61.8640 |
| 0.0285 | 1.1821 | 2700 | 1.3748| 31.91 | 47.58 | 61.8640 |
| 0.0292 | 1.2259 | 2800 | 1.3764| 31.92 | 47.96 | 61.1887 |
| 0.025 | 1.2697 | 2900 | 1.3799| 31.64 | 47.47 | 62.2242 |
| 0.0253 | 1.3135 | 3000 | 1.3732| 31.78 | 47.41 | 62.3143 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.2.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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