readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - accuracy
  model-index:
  - name: train
    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. -->
  
  # train
  
  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: 0.1100
  - F1: 0.6074
  - Roc Auc: 0.7538
  - Accuracy: 0.8966
  
  ## 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     | Roc Auc | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
  | 0.2023        | 1.0   | 5261  | 0.1159          | 0.5889 | 0.7525  | 0.8851   |
  | 0.1663        | 2.0   | 10522 | 0.1100          | 0.6074 | 0.7538  | 0.8966   |
  | 0.1472        | 3.0   | 15783 | 0.1132          | 0.5736 | 0.7679  | 0.8634   |
  | 0.1312        | 4.0   | 21044 | 0.1159          | 0.5975 | 0.7462  | 0.8911   |
  | 0.1175        | 5.0   | 26305 | 0.1289          | 0.5922 | 0.7390  | 0.8936   |
  | 0.1036        | 6.0   | 31566 | 0.1380          | 0.6062 | 0.7463  | 0.897    |
  | 0.089         | 7.0   | 36827 | 0.1440          | 0.5927 | 0.7395  | 0.894    |
  | 0.077         | 8.0   | 42088 | 0.1579          | 0.5998 | 0.7463  | 0.8944   |
  | 0.0661        | 9.0   | 47349 | 0.1662          | 0.5933 | 0.7382  | 0.8956   |
  | 0.0584        | 10.0  | 52610 | 0.1665          | 0.5940 | 0.7424  | 0.8922   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Tokenizers 0.13.2
  