readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice_8_0
  model-index:
  - name: Fine_Tunning_on_CV_Urdu_dataset
    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. -->
  
  # Fine_Tunning_on_CV_Urdu_dataset
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_8_0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2389
  - Wer: 0.7380
  
  ## 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: 100
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 15.2352       | 1.69  | 100  | 4.0555          | 1.0    |
  | 3.3873        | 3.39  | 200  | 3.2521          | 1.0    |
  | 3.2387        | 5.08  | 300  | 3.2304          | 1.0    |
  | 3.1983        | 6.78  | 400  | 3.1712          | 1.0    |
  | 3.1224        | 8.47  | 500  | 3.0883          | 1.0    |
  | 3.0782        | 10.17 | 600  | 3.0767          | 0.9996 |
  | 3.0618        | 11.86 | 700  | 3.0280          | 1.0    |
  | 2.9929        | 13.56 | 800  | 2.8994          | 1.0    |
  | 2.785         | 15.25 | 900  | 2.4330          | 1.0    |
  | 2.1276        | 16.95 | 1000 | 1.7795          | 0.9517 |
  | 1.5544        | 18.64 | 1100 | 1.5101          | 0.8266 |
  | 1.2651        | 20.34 | 1200 | 1.4037          | 0.7993 |
  | 1.0816        | 22.03 | 1300 | 1.3101          | 0.7638 |
  | 0.9817        | 23.73 | 1400 | 1.2855          | 0.7542 |
  | 0.9019        | 25.42 | 1500 | 1.2737          | 0.7421 |
  | 0.8688        | 27.12 | 1600 | 1.2457          | 0.7435 |
  | 0.8293        | 28.81 | 1700 | 1.2389          | 0.7380 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  