---
language:
- el
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-greek
  results: []
---

<!-- 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. -->

# wav2vec2-large-xls-r-300m-greek

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - EL dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6831
- Wer: 0.4287

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.0798        | 4.42  | 500   | 3.0010          | 1.0012 |
| 1.4336        | 8.85  | 1000  | 0.8481          | 0.6911 |
| 1.2062        | 13.27 | 1500  | 0.7312          | 0.6333 |
| 1.0481        | 17.7  | 2000  | 0.6850          | 0.5359 |
| 0.9837        | 22.12 | 2500  | 0.6337          | 0.5316 |
| 0.9108        | 26.55 | 3000  | 0.6258          | 0.5079 |
| 0.8439        | 30.97 | 3500  | 0.6301          | 0.4888 |
| 0.7901        | 35.4  | 4000  | 0.6245          | 0.4977 |
| 0.7669        | 39.82 | 4500  | 0.6164          | 0.4672 |
| 0.7196        | 44.25 | 5000  | 0.6039          | 0.4688 |
| 0.6715        | 48.67 | 5500  | 0.5900          | 0.4573 |
| 0.6441        | 53.1  | 6000  | 0.7002          | 0.4798 |
| 0.5938        | 57.52 | 6500  | 0.6249          | 0.4579 |
| 0.5541        | 61.95 | 7000  | 0.6184          | 0.4425 |
| 0.5506        | 66.37 | 7500  | 0.6963          | 0.4585 |
| 0.4998        | 70.8  | 8000  | 0.6778          | 0.4468 |
| 0.4729        | 75.22 | 8500  | 0.6383          | 0.4393 |
| 0.4535        | 79.65 | 9000  | 0.6593          | 0.4369 |
| 0.4358        | 84.07 | 9500  | 0.6914          | 0.4422 |
| 0.402         | 88.5  | 10000 | 0.6744          | 0.4269 |
| 0.3946        | 92.92 | 10500 | 0.6895          | 0.4275 |
| 0.3734        | 97.35 | 11000 | 0.6889          | 0.4320 |


### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0