---
language:
- el
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0,google/fleurs
metrics:
- wer
model-index:
- name: Whisper small Greek Farsipal and  El Greco
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr
      type: mozilla-foundation/common_voice_11_0,google/fleurs
      config: el
      split: None
    metrics:
    - name: Wer
      type: wer
      value: 17.199108469539375
---

<!-- 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 small Greek Farsioal and  El Greco

This model is a fine-tuned version of [emilios/whisper-sm-el-farsipal-e4](https://huggingface.co/emilios/whisper-sm-el-farsipal-e4) on the mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4871
- Wer: 17.1991

## 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-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1259        | 2.49  | 1000  | 0.4834          | 18.3692 |
| 0.1002        | 4.49  | 2000  | 0.4604          | 17.8027 |
| 0.1096        | 6.98  | 3000  | 0.4553          | 17.8770 |
| 0.0885        | 9.46  | 4000  | 0.4551          | 17.9606 |
| 0.0675        | 11.95 | 5000  | 0.4631          | 17.9049 |
| 0.0675        | 14.44 | 6000  | 0.4619          | 17.9049 |
| 0.0645        | 16.93 | 7000  | 0.4678          | 17.6727 |
| 0.0535        | 19.41 | 8000  | 0.4685          | 17.6634 |
| 0.039         | 21.49 | 9000  | 0.4746          | 17.6727 |
| 0.0447        | 23.98 | 10000 | 0.4761          | 17.6634 |
| 0.0393        | 26.46 | 11000 | 0.4792          | 17.7656 |
| 0.0308        | 28.95 | 12000 | 0.4851          | 17.8678 |
| 0.0301        | 31.44 | 13000 | 0.4846          | 17.4499 |
| 0.031         | 33.93 | 14000 | 0.4849          | 17.8306 |
| 0.0263        | 36.41 | 15000 | 0.4880          | 17.6170 |
| 0.0256        | 38.9  | 16000 | 0.4871          | 17.1991 |
| 0.0236        | 41.39 | 17000 | 0.4883          | 17.2641 |
| 0.0195        | 43.88 | 18000 | 0.4880          | 17.5706 |
| 0.0193        | 46.36 | 19000 | 0.4993          | 17.7285 |
| 0.0161        | 48.85 | 20000 | 0.4968          | 17.8306 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 2.0.0.dev20221216+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2