readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert-base-multilingual-uncased-finetuned-news
    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. -->
  
  # bert-base-multilingual-uncased-finetuned-news
  
  This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5705
  - Accuracy: 0.8896
  - F1: 0.8904
  
  ## 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: 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.5702        | 1.0   | 159  | 0.5156          | 0.7445   | 0.7553 |
  | 0.3384        | 2.0   | 318  | 0.2883          | 0.8612   | 0.8641 |
  | 0.2045        | 3.0   | 477  | 0.3699          | 0.8991   | 0.8977 |
  | 0.1177        | 4.0   | 636  | 0.5172          | 0.8959   | 0.8969 |
  | 0.0465        | 5.0   | 795  | 0.5705          | 0.8896   | 0.8904 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  