readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: muril-base-cased-finetuned-ours-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. -->
  
  # muril-base-cased-finetuned-ours-DS
  
  This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8885
  - Accuracy: 0.625
  - Precision: 0.5563
  - Recall: 0.5570
  - F1: 0.5412
  
  ## 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: 1e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 43
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 25
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 1.0904        | 1.98  | 99   | 1.0762          | 0.245    | 0.0817    | 0.3333 | 0.1312 |
  | 1.0535        | 3.96  | 198  | 1.0206          | 0.595    | 0.3940    | 0.5312 | 0.4410 |
  | 0.9936        | 5.94  | 297  | 1.0099          | 0.58     | 0.3582    | 0.4833 | 0.4115 |
  | 0.9371        | 7.92  | 396  | 0.9645          | 0.615    | 0.3918    | 0.5378 | 0.4507 |
  | 0.8931        | 9.9   | 495  | 0.9333          | 0.615    | 0.3969    | 0.5447 | 0.4535 |
  | 0.8237        | 11.88 | 594  | 0.9273          | 0.595    | 0.5451    | 0.5171 | 0.4439 |
  | 0.7772        | 13.86 | 693  | 0.8890          | 0.61     | 0.5186    | 0.5512 | 0.4661 |
  | 0.7365        | 15.84 | 792  | 0.8834          | 0.625    | 0.5661    | 0.5666 | 0.5112 |
  | 0.6987        | 17.82 | 891  | 0.9026          | 0.615    | 0.5532    | 0.5507 | 0.5314 |
  | 0.679         | 19.8  | 990  | 0.9018          | 0.63     | 0.5631    | 0.5596 | 0.5501 |
  | 0.6572        | 21.78 | 1089 | 0.8737          | 0.635    | 0.5782    | 0.5806 | 0.5614 |
  | 0.644         | 23.76 | 1188 | 0.8885          | 0.625    | 0.5563    | 0.5570 | 0.5412 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.10.1+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  