---
language:
- el
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- AMoustakis/test-dataset
metrics:
- wer
model-index:
- name: Whisper Base Greek
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Test Dataset for greek language
      type: AMoustakis/test-dataset
      args: 'split: train'
    metrics:
    - name: Wer
      type: wer
      value: 61.77777777777778
---

<!-- 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 Greek

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Test Dataset for greek language dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2675
- Wer: 61.7778

## 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: 0.001
- train_batch_size: 3
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.9014        | 1.0   | 4    | 0.5733          | 74.5185 |
| 0.4829        | 2.0   | 8    | 0.4158          | 64.4444 |
| 0.5963        | 3.0   | 12   | 0.3257          | 65.0370 |
| 0.3399        | 4.0   | 16   | 0.2857          | 61.7778 |
| 0.4436        | 5.0   | 20   | 0.2675          | 61.7778 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1