readme: ---
  language:
  - ga-IE
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - ga-IE
  - robust-speech-event
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: wav2vec-cv7-1b-ir
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: ga-IE
      metrics:
      - name: Test WER
        type: wer
        value: 39.1
      - name: Test CER
        type: cer
        value: 16.4
  ---
  
  <!-- 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-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - GA-IE dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9562
  - Wer: 0.4801
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 100.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.3731        | 15.62 | 500  | 1.5517          | 0.9499 |
  | 1.3312        | 31.25 | 1000 | 0.8717          | 0.6189 |
  | 0.9135        | 46.86 | 1500 | 0.8299          | 0.5310 |
  | 0.6719        | 62.49 | 2000 | 0.8842          | 0.5044 |
  | 0.5583        | 78.12 | 2500 | 0.9093          | 0.4801 |
  | 0.4728        | 93.74 | 3000 | 0.9488          | 0.4813 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  