readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: wav2vec2-large-lv60-self-colab
    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-lv60-self-colab
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-960h-lv60-self](https://huggingface.co/facebook/wav2vec2-large-960h-lv60-self) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0563
  - Wer: 0.1541
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 12
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 6.3084        | 1.0   | 500  | 3.0693          | 1.0    |
  | 1.5665        | 2.01  | 1000 | 0.0834          | 0.1749 |
  | 0.2761        | 3.01  | 1500 | 0.0620          | 0.1593 |
  | 0.178         | 4.02  | 2000 | 0.0667          | 0.1577 |
  | 0.1225        | 5.02  | 2500 | 0.0616          | 0.1587 |
  | 0.1423        | 6.02  | 3000 | 0.0581          | 0.1542 |
  | 0.1019        | 7.03  | 3500 | 0.0616          | 0.1559 |
  | 0.0914        | 8.03  | 4000 | 0.0690          | 0.1553 |
  | 0.0781        | 9.04  | 4500 | 0.0599          | 0.1541 |
  | 0.0791        | 10.04 | 5000 | 0.0607          | 0.1544 |
  | 0.0772        | 11.04 | 5500 | 0.0563          | 0.1541 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0+cu116
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  