readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: detect-femicide-news-xlmr-nl-mono-freeze2
    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. -->
  
  # detect-femicide-news-xlmr-nl-mono-freeze2
  
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6487
  - Accuracy: 0.6429
  - Precision Neg: 0.6429
  - Precision Pos: 0.0
  - Recall Neg: 1.0
  - Recall Pos: 0.0
  - F1 Score Neg: 0.7826
  - F1 Score Pos: 0.0
  
  ## 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: 1e-05
  - train_batch_size: 24
  - eval_batch_size: 8
  - seed: 1996
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 100
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Neg | Precision Pos | Recall Neg | Recall Pos | F1 Score Neg | F1 Score Pos |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:-------------:|:----------:|:----------:|:------------:|:------------:|
  | 0.7312        | 1.0   | 23   | 0.7413          | 0.3571   | 0.0           | 0.3571        | 0.0        | 1.0        | 0.0          | 0.5263       |
  | 0.7151        | 2.0   | 46   | 0.7177          | 0.3571   | 0.0           | 0.3571        | 0.0        | 1.0        | 0.0          | 0.5263       |
  | 0.7049        | 3.0   | 69   | 0.6988          | 0.3571   | 0.0           | 0.3571        | 0.0        | 1.0        | 0.0          | 0.5263       |
  | 0.6934        | 4.0   | 92   | 0.6945          | 0.3571   | 0.0           | 0.3571        | 0.0        | 1.0        | 0.0          | 0.5263       |
  | 0.6886        | 5.0   | 115  | 0.6903          | 0.6071   | 0.8182        | 0.4706        | 0.5        | 0.8        | 0.6207       | 0.5926       |
  | 0.6911        | 6.0   | 138  | 0.6846          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6856        | 7.0   | 161  | 0.6786          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6888        | 8.0   | 184  | 0.6783          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6862        | 9.0   | 207  | 0.6819          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6807        | 10.0  | 230  | 0.6758          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6839        | 11.0  | 253  | 0.6721          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6878        | 12.0  | 276  | 0.6708          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6799        | 13.0  | 299  | 0.6692          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6813        | 14.0  | 322  | 0.6673          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6792        | 15.0  | 345  | 0.6676          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6774        | 16.0  | 368  | 0.6683          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6807        | 17.0  | 391  | 0.6679          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6834        | 18.0  | 414  | 0.6693          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6784        | 19.0  | 437  | 0.6679          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.676         | 20.0  | 460  | 0.6698          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6791        | 21.0  | 483  | 0.6661          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6775        | 22.0  | 506  | 0.6633          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6688        | 23.0  | 529  | 0.6589          | 0.6429   | 0.6429        | 0.0           | 1.0        | 0.0        | 0.7826       | 0.0          |
  | 0.6748        | 24.0  | 552  | 0.6580          |