readme: ---
  license: cc-by-4.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: hing-roberta-finetuned-combined-DS
    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. -->
  
  # hing-roberta-finetuned-combined-DS
  
  This model is a fine-tuned version of [l3cube-pune/hing-roberta](https://huggingface.co/l3cube-pune/hing-roberta) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.0005
  - Accuracy: 0.6840
  - Precision: 0.6568
  - Recall: 0.6579
  - F1: 0.6570
  
  ## 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: 3.927975767245621e-05
  - train_batch_size: 8
  - eval_batch_size: 16
  - seed: 43
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.8684        | 1.0   | 1423 | 0.8762          | 0.6643   | 0.6561    | 0.6209 | 0.6215 |
  | 0.6545        | 2.0   | 2846 | 0.8043          | 0.6805   | 0.6497    | 0.6522 | 0.6502 |
  | 0.4267        | 3.0   | 4269 | 1.1337          | 0.6966   | 0.6668    | 0.6699 | 0.6680 |
  | 0.2762        | 4.0   | 5692 | 1.6520          | 0.6784   | 0.6558    | 0.6571 | 0.6553 |
  | 0.1535        | 5.0   | 7115 | 2.0005          | 0.6840   | 0.6568    | 0.6579 | 0.6570 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.10.1+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  