readme: ---
  language:
  - it
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - mozilla-foundation/common_voice_8_0
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: ''
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8.0
        type: mozilla-foundation/common_voice_8_0
        args: it
      metrics:
      - name: Test WER
        type: wer
        value: 100.0
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: it
      metrics:
      - name: Test WER
        type: wer
        value: 100.0
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: it
      metrics:
      - name: Test WER
        type: wer
        value: 100.0
  ---
  
  <!-- 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. -->
  
  # 
  
  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_8_0 - SV-SE dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3549
  - Wer: 0.3827
  
  ## 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: 7.5e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 2000
  - num_epochs: 50.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.4129        | 5.49  | 500  | 3.3224          | 1.0    |
  | 2.9323        | 10.98 | 1000 | 2.9128          | 1.0000 |
  | 1.6839        | 16.48 | 1500 | 0.7740          | 0.6854 |
  | 1.485         | 21.97 | 2000 | 0.5830          | 0.5976 |
  | 1.362         | 27.47 | 2500 | 0.4866          | 0.4905 |
  | 1.2752        | 32.96 | 3000 | 0.4240          | 0.4967 |
  | 1.1957        | 38.46 | 3500 | 0.3899          | 0.4258 |
  | 1.1646        | 43.95 | 4000 | 0.3597          | 0.4014 |
  | 1.1265        | 49.45 | 4500 | 0.3559          | 0.3829 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  