readme: ---
  license: cc-by-4.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: hing-roberta-NCM-run-3
    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-3
  
  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: 3.2053
  - Accuracy: 0.6645
  - Precision: 0.6565
  - Recall: 0.6479
  - F1: 0.6505
  
  ## 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.9077        | 1.0   | 927   | 0.8070          | 0.6397   | 0.6581    | 0.6439 | 0.6382 |
  | 0.6915        | 2.0   | 1854  | 0.8635          | 0.6462   | 0.6368    | 0.6439 | 0.6357 |
  | 0.4785        | 3.0   | 2781  | 1.0961          | 0.6613   | 0.6510    | 0.6556 | 0.6505 |
  | 0.3356        | 4.0   | 3708  | 1.6867          | 0.6667   | 0.6623    | 0.6611 | 0.6595 |
  | 0.2622        | 5.0   | 4635  | 2.0271          | 0.6602   | 0.6589    | 0.6451 | 0.6482 |
  | 0.1957        | 6.0   | 5562  | 2.2565          | 0.6634   | 0.6763    | 0.6517 | 0.6541 |
  | 0.1419        | 7.0   | 6489  | 2.4627          | 0.6440   | 0.6487    | 0.6203 | 0.6230 |
  | 0.1126        | 8.0   | 7416  | 2.7844          | 0.6483   | 0.6347    | 0.6268 | 0.6295 |
  | 0.091         | 9.0   | 8343  | 2.8776          | 0.6440   | 0.6302    | 0.6315 | 0.6307 |
  | 0.0758        | 10.0  | 9270  | 3.0246          | 0.6451   | 0.6325    | 0.6227 | 0.6256 |
  | 0.0674        | 11.0  | 10197 | 2.9389          | 0.6721   | 0.6605    | 0.6501 | 0.6530 |
  | 0.0542        | 12.0  | 11124 | 3.0503          | 0.6429   | 0.6456    | 0.6315 | 0.6330 |
  | 0.0576        | 13.0  | 12051 | 3.0252          | 0.6483   | 0.6427    | 0.6435 | 0.6398 |
  | 0.0337        | 14.0  | 12978 | 3.1160          | 0.6731   | 0.6676    | 0.6545 | 0.6575 |
  | 0.0318        | 15.0  | 13905 | 3.0740          | 0.6807   | 0.6733    | 0.6647 | 0.6671 |
  | 0.0188        | 16.0  | 14832 | 3.0890          | 0.6721   | 0.6633    | 0.6574 | 0.6589 |
  | 0.0258        | 17.0  | 15759 | 3.1519          | 0.6634   | 0.6602    | 0.6456 | 0.6490 |
  | 0.017         | 18.0  | 16686 | 3.1503          | 0.6688   | 0.6638    | 0.6547 | 0.6568 |
  | 0.0146        | 19.0  | 17613 | 3.2083          | 0.6688   | 0.6621    | 0.6516 | 0.6545 |
  | 0.0125        | 20.0  | 18540 | 3.2053          | 0.6645   | 0.6565    | 0.6479 | 0.6505 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.10.1+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  