readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: indic-gpt
    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. -->
  
  # indic-gpt
  
  This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an Indian Language(https://ai4bharat.iitm.ac.in/corpora) dataset. Sample Dataset is present on https://huggingface.co/datasets/aashay96/indic-gpt.
  It achieves the following results on the evaluation set:
  - Loss: 1.9482
  
  ## Model description
  
  Model is trained on multiple Indian Languages - Assamese, bengali, gujarati, Kannada, Malayalam,telugu, tamil, odhiya and punjabi.
  
  
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  TBD - Evaluation on indic_glue 
  
  ## Training procedure
  
  Check the notebook!
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 0.0005
  - train_batch_size: 128
  - eval_batch_size: 128
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 1024
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_steps: 100
  - num_epochs: 1
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 3.3653        | 0.3   | 500  | 2.2985          |
  | 2.2079        | 0.61  | 1000 | 2.0401          |
  | 2.0396        | 0.91  | 1500 | 1.9482          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  