readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: Fatwa-Topic-Classifier-xlm_roberta
    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. -->
  
  # Fatwa-Topic-Classifier-xlm_roberta
  
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0214
  - Accuracy: 0.6866
  - F1 Micro: 0.6866
  - F1 Macro: 0.4863
  - F1 Weighted: 0.6885
  - Precision Micro: 0.6866
  - Precision Macro: 0.5607
  - Precision Weighted: 0.6943
  - Recall Micro: 0.6866
  - Recall Macro: 0.4840
  - Recall Weighted: 0.6866
  
  ## 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: 2e-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: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Micro | F1 Macro | F1 Weighted | Precision Micro | Precision Macro | Precision Weighted | Recall Micro | Recall Macro | Recall Weighted |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|
  | 1.2743        | 1.0   | 4319  | 1.0864          | 0.6728   | 0.6728   | 0.3826   | 0.6597      | 0.6728          | 0.4398          | 0.6724             | 0.6728       | 0.3860       | 0.6728          |
  | 1.0044        | 2.0   | 8638  | 1.0301          | 0.6884   | 0.6884   | 0.4667   | 0.6859      | 0.6884          | 0.5082          | 0.6917             | 0.6884       | 0.4705       | 0.6884          |
  | 0.8326        | 3.0   | 12957 | 1.0214          | 0.6866   | 0.6866   | 0.4863   | 0.6885      | 0.6866          | 0.5607          | 0.6943             | 0.6866       | 0.4840       | 0.6866          |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  