readme: ---
  license: cc-by-4.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: hing-roberta-NCM-run-2
    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-NCM-run-2
  
  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: 3.3647
  - Accuracy: 0.6483
  - Precision: 0.6369
  - Recall: 0.6325
  - F1: 0.6341
  
  ## 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: 3e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.8973        | 1.0   | 927   | 0.8166          | 0.6483   | 0.6545    | 0.6576 | 0.6460 |
  | 0.6827        | 2.0   | 1854  | 0.9071          | 0.6526   | 0.6444    | 0.6261 | 0.6299 |
  | 0.4672        | 3.0   | 2781  | 1.1600          | 0.6764   | 0.6657    | 0.6634 | 0.6643 |
  | 0.3388        | 4.0   | 3708  | 1.7426          | 0.6548   | 0.6406    | 0.6442 | 0.6418 |
  | 0.2786        | 5.0   | 4635  | 1.9385          | 0.6505   | 0.6484    | 0.6437 | 0.6434 |
  | 0.1794        | 6.0   | 5562  | 2.3158          | 0.6472   | 0.6564    | 0.6365 | 0.6388 |
  | 0.12          | 7.0   | 6489  | 2.6961          | 0.6591   | 0.6458    | 0.6531 | 0.6466 |
  | 0.1298        | 8.0   | 7416  | 2.7196          | 0.6505   | 0.6523    | 0.6307 | 0.6342 |
  | 0.0941        | 9.0   | 8343  | 2.5853          | 0.6548   | 0.6406    | 0.6426 | 0.6415 |
  | 0.0696        | 10.0  | 9270  | 2.8386          | 0.6613   | 0.6616    | 0.6314 | 0.6348 |
  | 0.0722        | 11.0  | 10197 | 2.9658          | 0.6537   | 0.6356    | 0.6356 | 0.6355 |
  | 0.0509        | 12.0  | 11124 | 3.3286          | 0.6429   | 0.6262    | 0.6192 | 0.6214 |
  | 0.0444        | 13.0  | 12051 | 3.1654          | 0.6483   | 0.6347    | 0.6302 | 0.6319 |
  | 0.0341        | 14.0  | 12978 | 2.9509          | 0.6537   | 0.6430    | 0.6394 | 0.6401 |
  | 0.0345        | 15.0  | 13905 | 3.3416          | 0.6656   | 0.6514    | 0.6488 | 0.6499 |
  | 0.0303        | 16.0  | 14832 | 3.3874          | 0.6419   | 0.6267    | 0.6339 | 0.6272 |
  | 0.0245        | 17.0  | 15759 | 3.2854          | 0.6570   | 0.6428    | 0.6420 | 0.6421 |
  | 0.0174        | 18.0  | 16686 | 3.2863          | 0.6602   | 0.6569    | 0.6427 | 0.6465 |
  | 0.0136        | 19.0  | 17613 | 3.3674          | 0.6494   | 0.6361    | 0.6341 | 0.6349 |
  | 0.0111        | 20.0  | 18540 | 3.3647          | 0.6483   | 0.6369    | 0.6325 | 0.6341 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.10.1+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  