readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: muril-base-cased-finetuned-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-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: 0.9319
  - Accuracy: 0.6982
  - Precision: 0.6327
  - Recall: 0.6314
  - F1: 0.6320
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 1.0542        | 1.98  | 248  | 0.9786          | 0.5976   | 0.3936    | 0.5454 | 0.4330 |
  | 0.9307        | 3.97  | 496  | 0.8836          | 0.5996   | 0.4072    | 0.5604 | 0.4399 |
  | 0.8323        | 5.95  | 744  | 0.8266          | 0.5996   | 0.5508    | 0.5720 | 0.4527 |
  | 0.7554        | 7.94  | 992  | 0.8006          | 0.6318   | 0.5601    | 0.5838 | 0.5232 |
  | 0.6821        | 9.92  | 1240 | 0.8777          | 0.6740   | 0.5929    | 0.5875 | 0.5836 |
  | 0.6173        | 11.9  | 1488 | 0.8389          | 0.6640   | 0.5918    | 0.6031 | 0.5881 |
  | 0.5552        | 13.89 | 1736 | 0.9003          | 0.6962   | 0.6240    | 0.6160 | 0.6191 |
  | 0.4932        | 15.87 | 1984 | 0.8979          | 0.6982   | 0.6266    | 0.6231 | 0.6245 |
  | 0.4446        | 17.86 | 2232 | 0.9104          | 0.7002   | 0.6310    | 0.6290 | 0.6298 |
  | 0.4084        | 19.84 | 2480 | 0.9284          | 0.7002   | 0.6278    | 0.6255 | 0.6264 |
  | 0.3763        | 21.82 | 2728 | 0.9228          | 0.7082   | 0.6436    | 0.6380 | 0.6398 |
  | 0.3575        | 23.81 | 2976 | 0.9319          | 0.6982   | 0.6327    | 0.6314 | 0.6320 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.10.1+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  