readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-base-50k
    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-base-50k
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.5640
  - Wer: 1.0
  
  ## 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: 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: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer |
  |:-------------:|:-----:|:----:|:---------------:|:---:|
  | 10.7005       | 0.48  | 300  | 5.3021          | 1.0 |
  | 3.9938        | 0.96  | 600  | 3.4997          | 1.0 |
  | 3.591         | 1.44  | 900  | 3.5641          | 1.0 |
  | 3.6168        | 1.92  | 1200 | 3.5641          | 1.0 |
  | 3.6252        | 2.4   | 1500 | 3.5641          | 1.0 |
  | 3.6137        | 2.88  | 1800 | 3.5641          | 1.0 |
  | 3.6124        | 3.36  | 2100 | 3.5641          | 1.0 |
  | 3.6171        | 3.84  | 2400 | 3.5641          | 1.0 |
  | 3.6436        | 4.32  | 2700 | 3.5641          | 1.0 |
  | 3.6189        | 4.8   | 3000 | 3.5640          | 1.0 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  