readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: muril-base-cased-finetuned-TRAC-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-TRAC-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: 1.1894
  - Accuracy: 0.6838
  - Precision: 0.6534
  - Recall: 0.6513
  - F1: 0.6522
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 1.0109        | 1.99  | 612  | 0.9284          | 0.5948   | 0.4327    | 0.5193 | 0.4509 |
  | 0.8635        | 3.99  | 1224 | 0.8556          | 0.6291   | 0.6012    | 0.5865 | 0.5888 |
  | 0.764         | 5.98  | 1836 | 0.8585          | 0.6609   | 0.6249    | 0.6275 | 0.6260 |
  | 0.6744        | 7.97  | 2448 | 0.8469          | 0.6732   | 0.6391    | 0.6408 | 0.6398 |
  | 0.5865        | 9.97  | 3060 | 0.8438          | 0.6667   | 0.6424    | 0.6395 | 0.6395 |
  | 0.4978        | 11.96 | 3672 | 0.9269          | 0.6855   | 0.6532    | 0.6582 | 0.6542 |
  | 0.4245        | 13.95 | 4284 | 0.9934          | 0.6699   | 0.6397    | 0.6482 | 0.6396 |
  | 0.378         | 15.95 | 4896 | 1.0488          | 0.6830   | 0.6530    | 0.6446 | 0.6474 |
  | 0.3349        | 17.94 | 5508 | 1.0548          | 0.6806   | 0.6505    | 0.6536 | 0.6518 |
  | 0.3019        | 19.93 | 6120 | 1.1092          | 0.6757   | 0.6476    | 0.6497 | 0.6482 |
  | 0.2869        | 21.93 | 6732 | 1.1515          | 0.6814   | 0.6507    | 0.6514 | 0.6510 |
  | 0.2575        | 23.92 | 7344 | 1.1894          | 0.6838   | 0.6534    | 0.6513 | 0.6522 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.10.1+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  