readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: xlm-r-base-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. -->
  
  # xlm-r-base-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: 0.1995
  - Accuracy: 0.9624
  - F1: 0.9624
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 1.9235        | 1.0   | 1061 | 1.5991          | 0.6680   | 0.6680 |
  | 0.8738        | 2.0   | 2122 | 0.7982          | 0.8359   | 0.8359 |
  | 0.4406        | 3.0   | 3183 | 0.4689          | 0.9132   | 0.9132 |
  | 0.2534        | 4.0   | 4244 | 0.3165          | 0.9360   | 0.9360 |
  | 0.1593        | 5.0   | 5305 | 0.2434          | 0.9507   | 0.9507 |
  | 0.108         | 6.0   | 6366 | 0.2104          | 0.9599   | 0.9599 |
  | 0.0914        | 7.0   | 7427 | 0.1995          | 0.9624   | 0.9624 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  