readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: swadeshi_bhojpuriwav2vec2asr
    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. -->
  
  # swadeshi_bhojpuriwav2vec2asr
  
  This model is a fine-tuned version of [theainerd/Wav2Vec2-large-xlsr-hindi](https://huggingface.co/theainerd/Wav2Vec2-large-xlsr-hindi) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2155
  - Wer: 0.2931
  
  ## 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
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.6928        | 3.2   | 400  | 2.4820          | 0.9925 |
  | 1.6981        | 6.4   | 800  | 0.8053          | 0.6320 |
  | 0.975         | 9.6   | 1200 | 0.5420          | 0.4980 |
  | 0.7672        | 12.8  | 1600 | 0.4224          | 0.4233 |
  | 0.636         | 16.0  | 2000 | 0.3481          | 0.3774 |
  | 0.5562        | 19.2  | 2400 | 0.2861          | 0.3409 |
  | 0.4973        | 22.4  | 2800 | 0.2450          | 0.3211 |
  | 0.4616        | 25.6  | 3200 | 0.2230          | 0.3004 |
  | 0.4264        | 28.8  | 3600 | 0.2155          | 0.2931 |
  
  
  ### Framework versions
  
  - Transformers 4.20.0.dev0
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.3.dev0
  - Tokenizers 0.12.1
  