---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
base_model: openai/whisper-large-v2
model-index:
- name: whisper-large-v2-greek
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: fleurs
      type: fleurs
      config: el_gr
      split: test
      args: el_gr
    metrics:
    - type: wer
      value: 0.17739223993006523
      name: Wer
---

<!-- 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: 0.2734
- Wer Ortho: 0.2102
- Wer: 0.1774

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.1809        | 1.0   | 274  | 0.2244          | 0.2261    | 0.1947 |
| 0.0977        | 2.0   | 549  | 0.2306          | 0.2204    | 0.1856 |
| 0.0594        | 3.0   | 824  | 0.2332          | 0.2137    | 0.1814 |
| 0.0454        | 4.0   | 1099 | 0.2667          | 0.2315    | 0.1985 |
| 0.028         | 5.0   | 1374 | 0.2579          | 0.2151    | 0.1822 |
| 0.022         | 6.0   | 1649 | 0.2674          | 0.2188    | 0.1863 |
| 0.0202        | 6.98  | 1918 | 0.2734          | 0.2102    | 0.1774 |


### Framework versions

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