readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-large-xlsr-53_toy_train_fast_masked_augment_random_noise
    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-xlsr-53_toy_train_fast_masked_augment_random_noise
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3471
  - Wer: 0.4048
  
  ## 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: 0.0001
  - train_batch_size: 16
  - eval_batch_size: 8
  - 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: 15
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.0574        | 1.68  | 500  | 3.4185          | 0.9954 |
  | 1.45          | 3.36  | 1000 | 0.7043          | 0.7171 |
  | 0.8285        | 5.03  | 1500 | 0.3874          | 0.5050 |
  | 0.668         | 6.71  | 2000 | 0.3321          | 0.4512 |
  | 0.5324        | 8.39  | 2500 | 0.3394          | 0.4321 |
  | 0.4775        | 10.07 | 3000 | 0.3533          | 0.4231 |
  | 0.4421        | 11.74 | 3500 | 0.3487          | 0.4084 |
  | 0.441         | 13.42 | 4000 | 0.3471          | 0.4048 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu102
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  