readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: NLP_Project
    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. -->
  
  # NLP_Project
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5308
  - Wer: 0.3428
  
  ## 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: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 3.5939        | 1.0   | 500   | 2.1356          | 1.0014 |
  | 0.9126        | 2.01  | 1000  | 0.5469          | 0.5354 |
  | 0.4491        | 3.01  | 1500  | 0.4636          | 0.4503 |
  | 0.3008        | 4.02  | 2000  | 0.4269          | 0.4330 |
  | 0.2229        | 5.02  | 2500  | 0.4164          | 0.4073 |
  | 0.188         | 6.02  | 3000  | 0.4717          | 0.4107 |
  | 0.1739        | 7.03  | 3500  | 0.4306          | 0.4031 |
  | 0.159         | 8.03  | 4000  | 0.4394          | 0.3993 |
  | 0.1342        | 9.04  | 4500  | 0.4462          | 0.3904 |
  | 0.1093        | 10.04 | 5000  | 0.4387          | 0.3759 |
  | 0.1005        | 11.04 | 5500  | 0.5033          | 0.3847 |
  | 0.0857        | 12.05 | 6000  | 0.4805          | 0.3876 |
  | 0.0779        | 13.05 | 6500  | 0.5269          | 0.3810 |
  | 0.072         | 14.06 | 7000  | 0.5109          | 0.3710 |
  | 0.0641        | 15.06 | 7500  | 0.4865          | 0.3638 |
  | 0.0584        | 16.06 | 8000  | 0.5041          | 0.3646 |
  | 0.0552        | 17.07 | 8500  | 0.4987          | 0.3537 |
  | 0.0535        | 18.07 | 9000  | 0.4947          | 0.3586 |
  | 0.0475        | 19.08 | 9500  | 0.5237          | 0.3647 |
  | 0.042         | 20.08 | 10000 | 0.5338          | 0.3561 |
  | 0.0416        | 21.08 | 10500 | 0.5068          | 0.3483 |
  | 0.0358        | 22.09 | 11000 | 0.5126          | 0.3532 |
  | 0.0334        | 23.09 | 11500 | 0.5213          | 0.3536 |
  | 0.0331        | 24.1  | 12000 | 0.5378          | 0.3496 |
  | 0.03          | 25.1  | 12500 | 0.5167          | 0.3470 |
  | 0.0254        | 26.1  | 13000 | 0.5245          | 0.3418 |
  | 0.0233        | 27.11 | 13500 | 0.5393          | 0.3456 |
  | 0.0232        | 28.11 | 14000 | 0.5279          | 0.3425 |
  | 0.022         | 29.12 | 14500 | 0.5308          | 0.3428 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  