readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-300m-urdu-colab-cv8
    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-xls-r-300m-urdu-colab-cv8
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4651
  - Wer: 0.7
  
  ## 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: 0.0003
  - 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: 40
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 20.3271       | 1.27  | 32   | 20.3487         | 1.0    |
  | 11.0206       | 2.55  | 64   | 7.7343          | 1.0    |
  | 5.8023        | 3.82  | 96   | 5.4188          | 1.0    |
  | 4.5872        | 5.12  | 128  | 4.1428          | 1.0    |
  | 3.6691        | 6.39  | 160  | 3.4557          | 1.0    |
  | 3.3143        | 7.67  | 192  | 3.2663          | 1.0    |
  | 3.1689        | 8.94  | 224  | 3.1022          | 0.9982 |
  | 3.1472        | 10.24 | 256  | 3.0544          | 0.9993 |
  | 3.1091        | 11.51 | 288  | 3.0327          | 0.9978 |
  | 3.0437        | 12.78 | 320  | 3.0288          | 1.0    |
  | 2.9981        | 14.08 | 352  | 2.8645          | 1.0    |
  | 2.5244        | 15.35 | 384  | 2.0238          | 0.9686 |
  | 1.4962        | 16.63 | 416  | 1.5885          | 0.9118 |
  | 1.0138        | 17.9  | 448  | 1.3656          | 0.8155 |
  | 0.7655        | 19.2  | 480  | 1.4592          | 0.8125 |
  | 0.6267        | 20.47 | 512  | 1.4170          | 0.7867 |
  | 0.5127        | 21.75 | 544  | 1.3200          | 0.7716 |
  | 0.4422        | 23.04 | 576  | 1.4082          | 0.7727 |
  | 0.3482        | 24.31 | 608  | 1.3932          | 0.7432 |
  | 0.3128        | 25.59 | 640  | 1.4059          | 0.7432 |
  | 0.2762        | 26.86 | 672  | 1.4689          | 0.7336 |
  | 0.2451        | 28.16 | 704  | 1.4318          | 0.7207 |
  | 0.2104        | 29.43 | 736  | 1.4304          | 0.7399 |
  | 0.1858        | 30.71 | 768  | 1.4586          | 0.7225 |
  | 0.1779        | 31.98 | 800  | 1.4948          | 0.7284 |
  | 0.1546        | 33.27 | 832  | 1.4960          | 0.7173 |
  | 0.1457        | 34.55 | 864  | 1.4949          | 0.7077 |
  | 0.1333        | 35.82 | 896  | 1.4656          | 0.7085 |
  | 0.1212        | 37.12 | 928  | 1.5061          | 0.7033 |
  | 0.1162        | 38.39 | 960  | 1.4653          | 0.7055 |
  | 0.1043        | 39.67 | 992  | 1.4651          | 0.7    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  