---
library_name: transformers
language:
- el
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Baseline openai/whisper-tiny on Greek. Evaluated on 1701 audio samples
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_17_0- Greek
      type: mozilla-foundation/common_voice_17_0
      config: el
      split: None
      args: 'config: el, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 56.183418249189444
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Baseline openai/whisper-tiny on Greek. Evaluated on 1701 audio samples

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_17_0- Greek dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8397
- Wer: 56.1834

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.02          | 17.5439 | 1000 | 0.6888          | 56.2946 |
| 0.0024        | 35.0877 | 2000 | 0.8397          | 56.1834 |
| 0.001         | 52.6316 | 3000 | 0.9095          | 56.8041 |
| 0.0006        | 70.1754 | 4000 | 0.9501          | 57.0079 |
| 0.0005        | 87.7193 | 5000 | 0.9673          | 57.2487 |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0