readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: xlm-roberta-base-finetuned-peyma-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-peyma-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: 0.0937
  - F1: 0.9249
  
  ## 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.1562        | 1.0   | 998  | 0.0691          | 0.8777 |
  | 0.0638        | 2.0   | 1996 | 0.0703          | 0.8908 |
  | 0.0457        | 3.0   | 2994 | 0.0645          | 0.8975 |
  | 0.0281        | 4.0   | 3992 | 0.0842          | 0.8994 |
  | 0.0206        | 5.0   | 4990 | 0.0651          | 0.9164 |
  | 0.0139        | 6.0   | 5988 | 0.0787          | 0.9148 |
  | 0.0083        | 7.0   | 6986 | 0.0838          | 0.9253 |
  | 0.0052        | 8.0   | 7984 | 0.0833          | 0.9221 |
  | 0.0031        | 9.0   | 8982 | 0.0947          | 0.9230 |
  | 0.0028        | 10.0  | 9980 | 0.0937          | 0.9249 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.9.1
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  