---
language:
- el
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: whisper-large-v2-greek
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: FLEURS
      type: google/fleurs
      config: el_gr
      split: test
      args: el_gr
    metrics:
    - name: Wer
      type: wer
      value: 1.0564819086535293
---

<!-- 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-large-v2-greek

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the FLEURS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2061
- Wer Ortho: 1.0424
- Wer: 1.0565

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.1416        | 1.0   | 217  | 0.1611          | 1.2560    | 1.2638 |
| 0.0617        | 2.0   | 435  | 0.1612          | 1.1956    | 1.1930 |
| 0.027         | 3.0   | 653  | 0.1716          | 1.6495    | 1.6518 |
| 0.0155        | 4.0   | 871  | 0.1812          | 1.2816    | 1.2878 |
| 0.0114        | 5.0   | 1088 | 0.1792          | 1.0087    | 1.0071 |
| 0.0085        | 6.0   | 1306 | 0.1891          | 0.9757    | 0.9971 |
| 0.0073        | 7.0   | 1524 | 0.2017          | 1.0040    | 1.0225 |
| 0.0062        | 8.0   | 1742 | 0.1980          | 1.0737    | 1.0779 |
| 0.0094        | 9.0   | 1959 | 0.2103          | 0.8469    | 0.8459 |
| 0.0039        | 9.97  | 2170 | 0.2061          | 1.0424    | 1.0565 |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3