---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- bleu
- wer
model-index:
- name: Whisper Tiny GA-EN Speech Translation v.1.4
  results: []
datasets:
- ymoslem/IWSLT2023-GA-EN
language:
- ga
- en
---

<!-- 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 Tiny GA-EN Speech Translation v.1.4

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7420
- Bleu: 14.71
- Chrf: 30.02
- Wer: 95.7226

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Experiment

As this is a translation task into English, use `language="English"`

```
tokenizer = WhisperTokenizer.from_pretrained("openai/whisper-tiny",
                                             cache_dir=cache_dir,
                                             language="english",
                                             task="translate")
```

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- 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      |
|:-------------:|:-----:|:----:|:---------------:|:-----:|:-----:|:--------:|
| 0.8117        | 1.47  | 100  | 2.1773          | 8.81  | 24.15 | 119.9910 |
| 0.3555        | 2.94  | 200  | 2.2596          | 11.81 | 27.7  | 110.8510 |
| 0.0872        | 4.41  | 300  | 2.4108          | 12.89 | 28.57 | 110.5808 |
| 0.063         | 5.88  | 400  | 2.5306          | 12.67 | 27.78 | 107.1139 |
| 0.034         | 7.35  | 500  | 2.5784          | 17.0  | 30.42 | 85.8622  |
| 0.0349        | 8.82  | 600  | 2.6201          | 16.64 | 29.98 | 86.8978  |
| 0.0198        | 10.29 | 700  | 2.7151          | 16.0  | 30.04 | 88.2936  |
| 0.0134        | 11.76 | 800  | 2.7159          | 14.16 | 30.03 | 105.0878 |
| 0.0088        | 13.24 | 900  | 2.7369          | 14.61 | 29.32 | 94.3269  |
| 0.0056        | 14.71 | 1000 | 2.7420          | 14.71 | 30.02 | 95.7226  |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2