readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - wikiann
  metrics:
  - f1
  model-index:
  - name: xlm-roberta-base-finetuned-wikiann-hi
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: wikiann
        type: wikiann
        args: hi
      metrics:
      - name: F1
        type: f1
        value: 1.0
  ---
  
  <!-- 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-wikiann-hi
  
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the wikiann dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3097
  - F1: 1.0
  
  ## 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: 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  |
  |:-------------:|:-----:|:----:|:---------------:|:---:|
  | 0.5689        | 1.0   | 209  | 0.3179          | 1.0 |
  | 0.2718        | 2.0   | 418  | 0.2733          | 1.0 |
  | 0.19          | 3.0   | 627  | 0.2560          | 1.0 |
  | 0.142         | 4.0   | 836  | 0.2736          | 1.0 |
  | 0.0967        | 5.0   | 1045 | 0.2686          | 1.0 |
  | 0.0668        | 6.0   | 1254 | 0.2966          | 1.0 |
  | 0.052         | 7.0   | 1463 | 0.3194          | 1.0 |
  | 0.0369        | 8.0   | 1672 | 0.3034          | 1.0 |
  | 0.0236        | 9.0   | 1881 | 0.3174          | 1.0 |
  | 0.0135        | 10.0  | 2090 | 0.3097          | 1.0 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  