readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: xlm-roberta-base-language-detection-finetuned-ner
    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-language-detection-finetuned-ner
  
  This model is a fine-tuned version of [papluca/xlm-roberta-base-language-detection](https://huggingface.co/papluca/xlm-roberta-base-language-detection) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4885
  - Precision: 0.9273
  - Recall: 0.9644
  - F1: 0.9455
  - Accuracy: 0.9401
  
  ## 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: 6
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 289  | 0.0374          | 0.9912    | 0.9902 | 0.9907 | 0.9912   |
  | 0.1151        | 2.0   | 578  | 0.0147          | 0.9968    | 0.9971 | 0.9969 | 0.9965   |
  | 0.1151        | 3.0   | 867  | 0.0094          | 0.9984    | 0.9988 | 0.9986 | 0.9986   |
  | 0.0117        | 4.0   | 1156 | 0.0087          | 0.9982    | 0.9990 | 0.9986 | 0.9986   |
  | 0.0117        | 5.0   | 1445 | 0.0073          | 0.9986    | 0.9991 | 0.9989 | 0.9988   |
  | 0.0037        | 6.0   | 1734 | 0.0076          | 0.9984    | 0.9987 | 0.9986 | 0.9985   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  