readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: fedcsis-xlm_r-leyzer_en-intent
    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. -->
  
  # fedcsis-xlm_r-leyzer_en-intent
  
  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: 0.1846
  - Accuracy: 0.9617
  - F1: 0.9617
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 7
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 1.9001        | 1.0   | 1081 | 1.5709          | 0.6642   | 0.6642 |
  | 0.8845        | 2.0   | 2162 | 0.7658          | 0.8481   | 0.8481 |
  | 0.4549        | 3.0   | 3243 | 0.4535          | 0.9122   | 0.9122 |
  | 0.2515        | 4.0   | 4324 | 0.3097          | 0.9382   | 0.9382 |
  | 0.1529        | 5.0   | 5405 | 0.2317          | 0.9517   | 0.9517 |
  | 0.1122        | 6.0   | 6486 | 0.1956          | 0.9583   | 0.9583 |
  | 0.0841        | 7.0   | 7567 | 0.1846          | 0.9617   | 0.9617 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  