readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - xtreme
  metrics:
  - f1
  model-index:
  - name: xlm-roberta-base-finetuned-panx-de
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: xtreme
        type: xtreme
        config: PAN-X.de
        split: train
        args: PAN-X.de
      metrics:
      - name: F1
        type: f1
        value: 0.8766218984748463
  ---
  
  <!-- 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-finetuned-panx-de
  
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2123
  - F1: 0.8766
  
  ## 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: 24
  - eval_batch_size: 24
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.2657        | 1.0   | 525  | 0.1690          | 0.8133 |
  | 0.1409        | 2.0   | 1050 | 0.1438          | 0.8450 |
  | 0.0995        | 3.0   | 1575 | 0.1517          | 0.8473 |
  | 0.068         | 4.0   | 2100 | 0.1528          | 0.8590 |
  | 0.0503        | 5.0   | 2625 | 0.1663          | 0.8613 |
  | 0.0351        | 6.0   | 3150 | 0.1820          | 0.8703 |
  | 0.0245        | 7.0   | 3675 | 0.1853          | 0.8705 |
  | 0.0164        | 8.0   | 4200 | 0.1968          | 0.8743 |
  | 0.0102        | 9.0   | 4725 | 0.2087          | 0.8789 |
  | 0.0067        | 10.0  | 5250 | 0.2123          | 0.8766 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.11.0
  