---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- bleu
- wer
- chrf
model-index:
- name: Whisper Base GA-EN Speech Translation
  results: []
datasets:
- ymoslem/IWSLT2023-GA-EN
language:
- ga
- en
library_name: transformers
---

<!-- 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 Base GA-EN Speech Translation

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
The best model based on ChrF (this version) is at checkpoint 1000, epoch 3.72, and it achieves the following results on the evaluation set:
- Loss: 2.2482
- Bleu: 20.8
- Chrf: 35.56
- Wer: 84.0162

## 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: 32
- eval_batch_size: 32
- 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      |
|:-------------:|:-----:|:----:|:---------------:|:-----:|:-----:|:--------:|
| 1.5709        | 0.37  | 100  | 2.1099          | 5.49  | 22.56 | 144.5745 |
| 0.9426        | 0.74  | 200  | 2.0613          | 10.65 | 26.37 | 130.0315 |
| 0.3912        | 1.12  | 300  | 2.1207          | 13.43 | 29.77 | 103.9172 |
| 0.3943        | 1.49  | 400  | 2.1177          | 16.64 | 32.27 | 97.3435  |
| 0.3605        | 1.86  | 500  | 2.1689          | 18.41 | 32.69 | 87.1679  |
| 0.1164        | 2.23  | 600  | 2.1506          | 20.49 | 33.74 | 82.3953  |
| 0.1371        | 2.6   | 700  | 2.1397          | 19.86 | 34.97 | 84.9167  |
| 0.1263        | 2.97  | 800  | 2.1849          | 21.11 | 34.92 | 81.3147  |
| 0.049         | 3.35  | 900  | 2.2424          | 21.24 | 35.22 | 83.6110  |
| 0.0462        | 3.72  | 1000 | 2.2482          | 20.8  | 35.56 | 84.0162  |


### Framework versions

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