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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
metrics:
- bleu
- wer
model-index:
- name: Whisper Small GA-EN Speech Translation Raw + warmup_ratio=0.01
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: IWSLT-2023, FLEURS, BiteSize, and SpokenWords
type: ymoslem/IWSLT2023-GA-EN
metrics:
- name: Bleu
type: bleu
value: 30.07
- name: Wer
type: wer
value: 66.32147681224674
---
<!-- 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 Raw + warmup_ratio=0.01
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the IWSLT-2023, FLEURS, BiteSize, and SpokenWords dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7281
- Bleu: 30.07
- Chrf: 46.7
- Wer: 66.3215
## 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 | Validation Loss | Bleu | Chrf | Wer |
|:-------------:|:------:|:----:|:---------------:|:-----:|:-----:|:--------:|
| 2.1013 | 0.2155 | 100 | 1.8575 | 8.31 | 24.75 | 116.5241 |
| 1.5495 | 0.4310 | 200 | 1.5721 | 14.29 | 33.25 | 105.0428 |
| 1.3385 | 0.6466 | 300 | 1.5329 | 20.71 | 38.26 | 86.9428 |
| 1.071 | 0.8621 | 400 | 1.4540 | 20.37 | 39.28 | 85.1418 |
| 0.4771 | 1.0776 | 500 | 1.4936 | 18.05 | 39.17 | 93.8316 |
| 0.4685 | 1.2931 | 600 | 1.5303 | 24.36 | 39.36 | 75.6866 |
| 0.4477 | 1.5086 | 700 | 1.5242 | 22.93 | 42.01 | 80.3242 |
| 0.4238 | 1.7241 | 800 | 1.5052 | 26.32 | 43.01 | 68.8879 |
| 0.3802 | 1.9397 | 900 | 1.5171 | 25.94 | 41.44 | 73.7956 |
| 0.1429 | 2.1552 | 1000 | 1.5741 | 28.83 | 43.83 | 65.4660 |
| 0.1607 | 2.3707 | 1100 | 1.6029 | 27.67 | 43.2 | 64.9257 |
| 0.1513 | 2.5862 | 1200 | 1.6130 | 28.61 | 44.28 | 66.1864 |
| 0.137 | 2.8017 | 1300 | 1.6087 | 21.97 | 40.99 | 89.4642 |
| 0.112 | 3.0172 | 1400 | 1.6146 | 28.74 | 44.01 | 65.9613 |
| 0.0717 | 3.2328 | 1500 | 1.6156 | 27.3 | 42.78 | 70.0585 |
| 0.0596 | 3.4483 | 1600 | 1.6381 | 27.31 | 45.58 | 69.6983 |
| 0.064 | 3.6638 | 1700 | 1.6262 | 29.73 | 45.88 | 65.9163 |
| 0.0642 | 3.8793 | 1800 | 1.6798 | 30.78 | 46.13 | 68.2575 |
| 0.0335 | 4.0948 | 1900 | 1.6854 | 29.55 | 45.06 | 67.8523 |
| 0.0366 | 4.3103 | 2000 | 1.6963 | 28.83 | 44.42 | 68.8879 |
| 0.036 | 4.5259 | 2100 | 1.7062 | 28.05 | 43.79 | 69.6983 |
| 0.0259 | 4.7414 | 2200 | 1.7279 | 28.75 | 45.25 | 68.3926 |
| 0.0353 | 4.9569 | 2300 | 1.7084 | 29.7 | 46.13 | 66.3665 |
| 0.0138 | 5.1724 | 2400 | 1.6906 | 30.81 | 46.26 | 64.1603 |
| 0.0156 | 5.3879 | 2500 | 1.7135 | 29.09 | 45.94 | 67.4471 |
| 0.0133 | 5.6034 | 2600 | 1.7311 | 29.86 | 45.61 | 65.5110 |
| 0.0161 | 5.8190 | 2700 | 1.7067 | 29.5 | 45.22 | 67.0869 |
| 0.0098 | 6.0345 | 2800 | 1.7038 | 30.32 | 46.6 | 65.3309 |
| 0.008 | 6.25 | 2900 | 1.7261 | 29.88 | 46.41 | 66.8167 |
| 0.0045 | 6.4655 | 3000 | 1.7281 | 30.07 | 46.7 | 66.3215 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.2.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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