---
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
- ymoslem/FLEURS-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 (this version) is at checkpoint 1000, epoch 2.54, and it achieves the following results on the evaluation set:
- Loss: 1.9005
- Bleu: 21.83
- Chrf: 37.13
- Wer: 80.4593

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Experiment

- Data (v1.1: IWSLT2023-GA-EN; v1.2: +FLEURS-GA-EN)

### 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      |
|:-------------:|:-----:|:----:|:---------------:|:-----:|:-----:|:--------:|
| 2.6826        | 0.25  | 100  | 2.0993          | 7.23  | 22.29 | 100.7654 |
| 2.1287        | 0.51  | 200  | 1.9451          | 9.37  | 27.74 | 125.9343 |
| 1.8482        | 0.76  | 300  | 1.8356          | 13.11 | 30.65 | 103.5570 |
| 1.2977        | 1.02  | 400  | 1.8643          | 10.56 | 30.86 | 128.5907 |
| 0.8068        | 1.27  | 500  | 1.8658          | 18.23 | 35.17 | 82.6204  |
| 0.7257        | 1.52  | 600  | 1.8493          | 17.81 | 34.13 | 90.7249  |
| 0.6202        | 1.78  | 700  | 1.8312          | 17.6  | 35.19 | 92.2107  |
| 0.4348        | 2.03  | 800  | 1.8771          | 17.9  | 35.66 | 91.9856  |
| 0.2566        | 2.28  | 900  | 1.9088          | 20.14 | 36.79 | 81.4498  |
| 0.2301        | 2.54  | 1000 | 1.9005          | 21.83 | 37.13 | 80.4593  |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2