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---
language:
- ga
- en
license: apache-2.0
base_model: openai/whisper-medium
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: 33.1
- name: Wer
type: wer
value: 62.40432237730752
---
<!-- 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-medium](https://huggingface.co/openai/whisper-medium) on the IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1873
- Bleu: 33.1
- Chrf: 51.85
- Wer: 62.4043
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.02
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Wer |
|:-------------:|:------:|:----:|:---------------:|:-----:|:-----:|:--------:|
| 2.6291 | 0.0109 | 100 | 2.1971 | 2.33 | 16.34 | 175.5516 |
| 2.6591 | 0.0219 | 200 | 2.0357 | 5.57 | 22.49 | 122.2873 |
| 2.5637 | 0.0328 | 300 | 1.8690 | 7.67 | 26.29 | 133.0032 |
| 2.2954 | 0.0438 | 400 | 1.8062 | 11.2 | 30.03 | 114.2278 |
| 2.3292 | 0.0547 | 500 | 1.7421 | 9.85 | 29.28 | 117.2895 |
| 2.1223 | 0.0657 | 600 | 1.6739 | 14.56 | 32.56 | 84.2864 |
| 2.2398 | 0.0766 | 700 | 1.7187 | 13.86 | 34.74 | 98.9644 |
| 2.002 | 0.0876 | 800 | 1.6392 | 15.53 | 36.64 | 96.7582 |
| 1.8611 | 0.0985 | 900 | 1.6283 | 15.8 | 36.32 | 94.3719 |
| 1.8498 | 0.1095 | 1000 | 1.6102 | 17.58 | 36.0 | 85.5921 |
| 1.7585 | 0.1204 | 1100 | 1.6337 | 15.91 | 36.61 | 100.2251 |
| 1.6115 | 0.1314 | 1200 | 1.5381 | 22.21 | 39.94 | 76.8122 |
| 1.4415 | 0.1423 | 1300 | 1.5864 | 20.36 | 37.87 | 79.1986 |
| 1.5103 | 0.1533 | 1400 | 1.4925 | 23.2 | 41.26 | 75.2364 |
| 1.6576 | 0.1642 | 1500 | 1.4508 | 18.12 | 40.49 | 102.9266 |
| 1.3429 | 0.1752 | 1600 | 1.4399 | 27.88 | 43.74 | 69.7884 |
| 1.2522 | 0.1861 | 1700 | 1.4256 | 23.04 | 43.31 | 77.1724 |
| 1.2018 | 0.1970 | 1800 | 1.4072 | 21.06 | 40.39 | 78.6583 |
| 1.1945 | 0.2080 | 1900 | 1.4222 | 23.0 | 42.71 | 76.7222 |
| 1.1869 | 0.2189 | 2000 | 1.3992 | 22.54 | 42.02 | 75.8667 |
| 1.1752 | 0.2299 | 2100 | 1.3926 | 20.81 | 41.07 | 79.5137 |
| 1.0281 | 0.2408 | 2200 | 1.3633 | 27.24 | 45.55 | 69.6083 |
| 0.894 | 0.2518 | 2300 | 1.3287 | 28.6 | 45.58 | 65.8712 |
| 0.9788 | 0.2627 | 2400 | 1.3138 | 27.75 | 46.21 | 69.2931 |
| 0.8418 | 0.2737 | 2500 | 1.3064 | 27.85 | 46.17 | 68.3026 |
| 0.7559 | 0.2846 | 2600 | 1.2903 | 28.44 | 48.52 | 68.3476 |
| 0.8632 | 0.2956 | 2700 | 1.2834 | 27.87 | 46.86 | 68.3476 |
| 0.7501 | 0.3065 | 2800 | 1.2669 | 28.63 | 49.25 | 68.5277 |
| 0.6953 | 0.3175 | 2900 | 1.2615 | 30.46 | 48.83 | 64.4304 |
| 0.7195 | 0.3284 | 3000 | 1.2514 | 27.49 | 47.94 | 71.0941 |
| 0.6155 | 0.3394 | 3100 | 1.2428 | 30.06 | 49.64 | 66.5916 |
| 0.605 | 0.3503 | 3200 | 1.2040 | 31.64 | 50.27 | 63.8451 |
| 0.6349 | 0.3612 | 3300 | 1.2077 | 28.96 | 49.35 | 65.3760 |
| 0.4669 | 0.3722 | 3400 | 1.2219 | 31.17 | 48.95 | 64.2503 |
| 0.5196 | 0.3831 | 3500 | 1.2124 | 30.97 | 50.13 | 63.8001 |
| 0.5141 | 0.3941 | 3600 | 1.2026 | 31.97 | 50.8 | 63.0347 |
| 0.4221 | 0.4050 | 3700 | 1.1893 | 31.76 | 51.35 | 63.4399 |
| 0.2951 | 0.4160 | 3800 | 1.2049 | 32.4 | 51.08 | 63.1247 |
| 0.3898 | 0.4269 | 3900 | 1.1906 | 32.15 | 51.09 | 63.5299 |
| 0.4071 | 0.4379 | 4000 | 1.1873 | 33.1 | 51.85 | 62.4043 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.2.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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