readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: muril-base-cased-finetuned-non-code-mixed-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-non-code-mixed-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: 1.2867
  - Accuracy: 0.6214
  - Precision: 0.6081
  - Recall: 0.6009
  - F1: 0.6034
  
  ## 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
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 25
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 1.0861        | 2.0   | 463  | 1.0531          | 0.3506   | 0.1169    | 0.3333 | 0.1731 |
  | 0.99          | 3.99  | 926  | 0.9271          | 0.5836   | 0.4310    | 0.5200 | 0.4502 |
  | 0.8759        | 5.99  | 1389 | 0.9142          | 0.5965   | 0.5788    | 0.5907 | 0.5802 |
  | 0.7726        | 7.98  | 1852 | 0.8726          | 0.6095   | 0.6079    | 0.6078 | 0.6027 |
  | 0.6659        | 9.98  | 2315 | 0.9145          | 0.6246   | 0.6139    | 0.6174 | 0.6140 |
  | 0.5727        | 11.97 | 2778 | 0.9606          | 0.6311   | 0.6180    | 0.6109 | 0.6133 |
  | 0.4889        | 13.97 | 3241 | 1.0342          | 0.6170   | 0.6059    | 0.6054 | 0.6045 |
  | 0.4267        | 15.97 | 3704 | 1.0539          | 0.6170   | 0.6089    | 0.6081 | 0.6066 |
  | 0.3751        | 17.96 | 4167 | 1.1740          | 0.6343   | 0.6255    | 0.6074 | 0.6112 |
  | 0.3402        | 19.96 | 4630 | 1.2021          | 0.6192   | 0.6078    | 0.6013 | 0.6031 |
  | 0.318         | 21.95 | 5093 | 1.2875          | 0.6181   | 0.6007    | 0.5946 | 0.5965 |
  | 0.2977        | 23.95 | 5556 | 1.2867          | 0.6214   | 0.6081    | 0.6009 | 0.6034 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.10.1+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  