readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: Project_NLP
    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. -->
  
  # Project_NLP
  
  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: 0.5324
  - Wer: 0.3355
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 3.5697        | 1.0   | 500   | 2.1035          | 0.9979 |
  | 0.8932        | 2.01  | 1000  | 0.5649          | 0.5621 |
  | 0.4363        | 3.01  | 1500  | 0.4326          | 0.4612 |
  | 0.3035        | 4.02  | 2000  | 0.4120          | 0.4191 |
  | 0.2343        | 5.02  | 2500  | 0.4199          | 0.3985 |
  | 0.1921        | 6.02  | 3000  | 0.4380          | 0.4043 |
  | 0.1549        | 7.03  | 3500  | 0.4456          | 0.3925 |
  | 0.1385        | 8.03  | 4000  | 0.4264          | 0.3871 |
  | 0.1217        | 9.04  | 4500  | 0.4744          | 0.3774 |
  | 0.1041        | 10.04 | 5000  | 0.4498          | 0.3745 |
  | 0.0968        | 11.04 | 5500  | 0.4716          | 0.3628 |
  | 0.0893        | 12.05 | 6000  | 0.4680          | 0.3764 |
  | 0.078         | 13.05 | 6500  | 0.5100          | 0.3623 |
  | 0.0704        | 14.06 | 7000  | 0.4893          | 0.3552 |
  | 0.0659        | 15.06 | 7500  | 0.4956          | 0.3565 |
  | 0.0578        | 16.06 | 8000  | 0.5450          | 0.3595 |
  | 0.0563        | 17.07 | 8500  | 0.4891          | 0.3614 |
  | 0.0557        | 18.07 | 9000  | 0.5307          | 0.3548 |
  | 0.0447        | 19.08 | 9500  | 0.4923          | 0.3493 |
  | 0.0456        | 20.08 | 10000 | 0.5156          | 0.3479 |
  | 0.0407        | 21.08 | 10500 | 0.4979          | 0.3389 |
  | 0.0354        | 22.09 | 11000 | 0.5549          | 0.3462 |
  | 0.0322        | 23.09 | 11500 | 0.5601          | 0.3439 |
  | 0.0342        | 24.1  | 12000 | 0.5131          | 0.3451 |
  | 0.0276        | 25.1  | 12500 | 0.5206          | 0.3392 |
  | 0.0245        | 26.1  | 13000 | 0.5337          | 0.3373 |
  | 0.0226        | 27.11 | 13500 | 0.5311          | 0.3353 |
  | 0.0229        | 28.11 | 14000 | 0.5375          | 0.3373 |
  | 0.0225        | 29.12 | 14500 | 0.5324          | 0.3355 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  