readme: ---
  license: mit
  tags:
  - generated_from_trainer
  - token-classification
  datasets:
  - xtreme
  metrics:
  - f1
  model-index:
  - name: xlm-roberta-base-finetuned-arman-fa
    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. -->
  
  # xlm-roberta-base-finetuned-arman-fa
  
  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: 0.0077
  - F1: 0.9855
  
  ## 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: 5e-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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.1054        | 1.0   | 2305  | 0.0497          | 0.8548 |
  | 0.0419        | 2.0   | 4610  | 0.0339          | 0.8834 |
  | 0.0185        | 3.0   | 6915  | 0.0159          | 0.9626 |
  | 0.0068        | 4.0   | 9220  | 0.0103          | 0.9789 |
  | 0.0025        | 5.0   | 11525 | 0.0077          | 0.9855 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.9.1
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  