---
language:
- el
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
- hf-asr-leaderboard
- automatic-speech-recognition
- greek
datasets:
- mozilla-foundation/common_voice_11_0
- google/fleurs
metrics:
- wer
model-index:
- name: whisper-md-el-intlv-xs
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0
      type: mozilla-foundation/common_voice_11_0
      config: el
      split: test
    metrics:
    - name: Wer
      type: wer
      value: 11.3670
---


# whisper-md-el-intlv-xs

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on interleaved mozilla-foundation/common_voice_11_0 (el) and the google/fleurs (el_gr) datasets. It achieves the following results on the mozilla-foundation/common_voice_11_0 test evaluation set:
- Loss: 0.4168
- Wer: 11.3670

## Model description

This model is trained over the two interleaved datasets in the Greek language. Testing used only the common_voice_11_0 (el) test split.

## Intended uses & limitations

The model was trained for transcription in Greek 

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 8e-06
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0251        | 2.49  | 1000  | 0.2216          | 12.5836 |
| 0.0051        | 4.98  | 2000  | 0.2874          | 12.2957 |
| 0.0015        | 7.46  | 3000  | 0.3281          | 11.9056 |
| 0.0017        | 9.95  | 4000  | 0.3178          | 12.5929 |
| 0.0008        | 12.44 | 5000  | 0.3449          | 11.9799 |
| 0.0001        | 14.93 | 6000  | 0.3638          | 11.7106 |
| 0.0001        | 17.41 | 7000  | 0.3910          | 11.4970 |
| 0.0           | 19.9  | 8000  | 0.4042          | 11.3949 |
| 0.0           | 22.39 | 9000  | 0.4129          | 11.4134 |
| 0.0           | 24.88 | 10000 | 0.4168          | 11.3670 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2