README.md

---
language:
- el
license: apache-2.0
tags:
- whisper-event
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: whisper-small-el
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 el
      type: mozilla-foundation/common_voice_11_0
      config: el
      split: test
      args: el
    metrics:
    - name: Wer
      type: wer
      value: 25.696508172362552
---

# Whisper Small - Greek (el)

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 el dataset 
for transcription in Greek.
It achieves the following results on the evaluation set:

- train_loss: 0.0615
- Wer: 20.2080


### Training results

Upon completion of training the best model was reloaded and tested with the following results extracted from the stdout log:
```
Loading best model from ./whisper-small-el/checkpoint-5000 (score: 20.208023774145616).

{'train_runtime': 73232.697,
'train_samples_per_second': 4.37,
'train_steps_per_second': 0.068,
'train_loss': 0.06146362095708027,
'epoch': 94.34}

TrainOutput(global_step=5000,
    training_loss=0.06146362095708027,
    metrics={'train_runtime': 73232.697,
        'train_samples_per_second': 4.37,
        'train_steps_per_second': 0.068,
        'train_loss': 0.06146362095708027,
        'epoch': 94.34})
```

### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.12.1