readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: egy-slang-model
    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. -->
  
  # egy-slang-model
  
  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: 2.9273
  - Wer: 1.0000
  
  ## 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: 0.001
  - 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: 500
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.64  | 200  | 2.9735          | 1.0    |
  | 3.8098        | 3.28  | 400  | 2.9765          | 1.0    |
  | 3.8098        | 4.91  | 600  | 2.9662          | 1.0    |
  | 2.9531        | 6.56  | 800  | 2.9708          | 1.0    |
  | 2.9531        | 8.2   | 1000 | 2.9673          | 1.0    |
  | 2.9259        | 9.83  | 1200 | 2.9989          | 1.0    |
  | 2.9259        | 11.47 | 1400 | 2.9889          | 1.0    |
  | 2.9023        | 13.11 | 1600 | 2.9739          | 1.0    |
  | 2.9023        | 14.75 | 1800 | 3.0040          | 1.0000 |
  | 2.8832        | 16.39 | 2000 | 3.0170          | 1.0    |
  | 2.8832        | 18.03 | 2200 | 2.9963          | 0.9999 |
  | 2.8691        | 19.67 | 2400 | 2.9273          | 1.0000 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.1
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  