readme: ---
  language:
  - el
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - el
  - robust-speech-event
  - model_for_talk
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: XLS-R-300M - Greek
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: el
      metrics:
      - name: Test WER
        type: wer
        value: 102.23963133640552
      - name: Test CER
        type: cer
        value: 146.28
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: el
      metrics:
      - name: Test WER
        type: wer
        value: 99.92
      - name: Test CER
        type: cer
        value: 132.38
  ---
  
  <!-- 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: 0.6592
  - Wer: 0.4564
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 3.0928        | 4.42  | 500   | 3.0804          | 1.0073 |
  | 1.4505        | 8.85  | 1000  | 0.9038          | 0.7330 |
  | 1.2207        | 13.27 | 1500  | 0.7375          | 0.6045 |
  | 1.0695        | 17.7  | 2000  | 0.7119          | 0.5441 |
  | 1.0104        | 22.12 | 2500  | 0.6069          | 0.5296 |
  | 0.9299        | 26.55 | 3000  | 0.6168          | 0.5206 |
  | 0.8588        | 30.97 | 3500  | 0.6382          | 0.5171 |
  | 0.7942        | 35.4  | 4000  | 0.6048          | 0.4988 |
  | 0.7808        | 39.82 | 4500  | 0.6730          | 0.5084 |
  | 0.743         | 44.25 | 5000  | 0.6749          | 0.5012 |
  | 0.6652        | 48.67 | 5500  | 0.6491          | 0.4735 |
  | 0.6386        | 53.1  | 6000  | 0.6928          | 0.4954 |
  | 0.5945        | 57.52 | 6500  | 0.6359          | 0.4798 |
  | 0.5561        | 61.95 | 7000  | 0.6409          | 0.4799 |
  | 0.5464        | 66.37 | 7500  | 0.6452          | 0.4691 |
  | 0.5119        | 70.8  | 8000  | 0.6376          | 0.4657 |
  | 0.474         | 75.22 | 8500  | 0.6541          | 0.4700 |
  | 0.45          | 79.65 | 9000  | 0.6374          | 0.4571 |
  | 0.4315        | 84.07 | 9500  | 0.6568          | 0.4625 |
  | 0.3967        | 88.5  | 10000 | 0.6636          | 0.4605 |
  | 0.3937        | 92.92 | 10500 | 0.6537          | 0.4597 |
  | 0.3788        | 97.35 | 11000 | 0.6614          | 0.4589 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.11.0
  