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---
language:
- ga
- en
license: apache-2.0
base_model: openai/whisper-large-v3
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
- ymoslem/EUbookshop-Speech-Irish
metrics:
- bleu
- wer
model-index:
- name: Whisper Larget V3 GA-EN Speech Translation
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, Wikimedia, and EUbookshop
type: ymoslem/IWSLT2023-GA-EN
metrics:
- name: Bleu
type: bleu
value: 15.23
- name: Wer
type: wer
value: 92.70598829356146
---
<!-- 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 Larget V3 GA-EN Speech Translation
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, Wikimedia, and EUbookshop dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9885
- Bleu: 15.23
- Chrf: 28.15
- Wer: 92.7060
## 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: 0.03
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Bleu | Chrf | Validation Loss | Wer |
|:-------------:|:------:|:----:|:-----:|:-----:|:---------------:|:--------:|
| 2.5918 | 0.0138 | 100 | 0.61 | 8.48 | 2.1791 | 238.2260 |
| 2.476 | 0.0276 | 200 | 0.63 | 10.43 | 2.1702 | 275.7317 |
| 2.2358 | 0.0414 | 300 | 4.76 | 19.98 | 2.0420 | 120.0810 |
| 2.1778 | 0.0552 | 400 | 2.78 | 12.85 | 1.9506 | 86.8528 |
| 1.9779 | 0.0690 | 500 | 4.53 | 18.47 | 1.8609 | 137.1905 |
| 1.9435 | 0.0828 | 600 | 6.67 | 22.37 | 1.7726 | 82.4403 |
| 1.7928 | 0.0966 | 700 | 4.54 | 17.32 | 1.7445 | 133.8586 |
| 1.9004 | 0.1103 | 800 | 1.58 | 12.65 | 1.7290 | 195.2724 |
| 1.7856 | 0.1241 | 900 | 4.84 | 17.5 | 1.6990 | 83.9262 |
| 1.6783 | 0.1379 | 1000 | 8.46 | 24.24 | 1.6329 | 113.5074 |
| 1.6095 | 0.1517 | 1100 | 7.35 | 20.22 | 1.6083 | 102.5214 |
| 1.6328 | 0.1655 | 1200 | 11.46 | 25.29 | 1.5267 | 76.5871 |
| 1.6093 | 0.1793 | 1300 | 6.51 | 17.77 | 1.4947 | 112.4719 |
| 1.5776 | 0.1931 | 1400 | 6.21 | 19.86 | 1.4952 | 90.6348 |
| 1.4767 | 0.2069 | 1500 | 4.86 | 19.57 | 1.4515 | 145.1148 |
| 1.3447 | 0.2207 | 1600 | 6.77 | 19.96 | 1.3974 | 90.5448 |
| 1.3273 | 0.2345 | 1700 | 4.77 | 16.31 | 1.4323 | 152.1837 |
| 1.4253 | 0.2483 | 1800 | 3.95 | 15.66 | 1.3598 | 173.2553 |
| 1.3505 | 0.2621 | 1900 | 11.25 | 23.4 | 1.3517 | 80.3692 |
| 1.2593 | 0.2759 | 2000 | 12.71 | 26.55 | 1.3236 | 77.5777 |
| 1.2483 | 0.2897 | 2100 | 17.88 | 32.0 | 1.2825 | 73.3003 |
| 1.161 | 0.3034 | 2200 | 10.08 | 20.69 | 1.2567 | 115.8937 |
| 1.1597 | 0.3172 | 2300 | 8.61 | 19.54 | 1.2581 | 93.8766 |
| 1.0937 | 0.3310 | 2400 | 12.37 | 25.67 | 1.2577 | 99.0095 |
| 1.0606 | 0.3448 | 2500 | 6.46 | 23.47 | 1.2228 | 172.9401 |
| 1.039 | 0.3586 | 2600 | 9.55 | 21.56 | 1.2186 | 89.7794 |
| 1.0193 | 0.3724 | 2700 | 3.08 | 17.58 | 1.1844 | 281.8100 |
| 1.1153 | 0.3862 | 2800 | 1.1693| 2.69 | 18.38 | 350.2927 |
| 1.012 | 0.4 | 2900 | 1.1233| 3.56 | 14.74 | 194.9122 |
| 0.8936 | 0.4138 | 3000 | 1.1161| 5.21 | 17.38 | 158.3521 |
| 0.8893 | 0.4276 | 3100 | 1.1119| 11.52 | 25.02 | 80.9095 |
| 0.9491 | 0.4414 | 3200 | 1.1213| 5.93 | 20.91 | 174.0207 |
| 0.9233 | 0.4552 | 3300 | 1.0656| 5.54 | 20.95 | 186.2224 |
| 0.8915 | 0.4690 | 3400 | 1.0736| 7.26 | 23.99 | 155.6506 |
| 0.8296 | 0.4828 | 3500 | 1.0461| 6.74 | 21.46 | 146.1054 |
| 0.8163 | 0.4966 | 3600 | 1.0706| 11.35 | 24.11 | 101.8010 |
| 0.8115 | 0.5103 | 3700 | 1.0199| 12.84 | 26.92 | 115.8487 |
| 0.8245 | 0.5241 | 3800 | 1.0163| 12.47 | 24.29 | 101.9361 |
| 0.7988 | 0.5379 | 3900 | 0.9891| 15.29 | 28.54 | 92.7960 |
| 0.769 | 0.5517 | 4000 | 0.9885| 15.23 | 28.15 | 92.7060 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2+git70dfd51
- Datasets 2.20.0
- Tokenizers 0.19.1
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