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---
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
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