readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: wav2vec2-large-xls-r-300m-telugu-asr
    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-telugu-asr
  
  This model is a fine-tuned version of [henilp105/wav2vec2-large-xls-r-300m-telugu-asr](https://huggingface.co/henilp105/wav2vec2-large-xls-r-300m-telugu-asr) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1050
  - Wer: 0.6656
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 6.0506        | 2.3   | 200  | 0.8841          | 0.7564 |
  | 0.6354        | 4.59  | 400  | 0.7448          | 0.6912 |
  | 0.3934        | 6.89  | 600  | 0.8321          | 0.6929 |
  | 0.2652        | 9.19  | 800  | 0.9529          | 0.6984 |
  | 0.2022        | 11.49 | 1000 | 0.9490          | 0.6979 |
  | 0.1514        | 13.79 | 1200 | 1.0025          | 0.6869 |
  | 0.124         | 16.09 | 1400 | 1.0367          | 0.6799 |
  | 0.1007        | 18.39 | 1600 | 1.0658          | 0.6734 |
  | 0.0875        | 20.69 | 1800 | 1.0758          | 0.6779 |
  | 0.0838        | 22.98 | 2000 | 1.0999          | 0.6701 |
  | 0.0745        | 25.29 | 2200 | 1.1020          | 0.6708 |
  | 0.0641        | 27.58 | 2400 | 1.1140          | 0.6683 |
  | 0.0607        | 29.88 | 2600 | 1.1050          | 0.6656 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  