readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert-base-multilingual-uncased-finetuned-masress
    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-masress
  
  This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0946
  - Accuracy: 0.5782
  - F1: 0.5769
  
  ## 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: 64
  - eval_batch_size: 64
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 1.1646        | 1.0   | 151  | 1.0626          | 0.5588   | 0.5566 |
  | 0.9281        | 2.0   | 302  | 0.9800          | 0.5869   | 0.5792 |
  | 0.8269        | 3.0   | 453  | 1.0134          | 0.5911   | 0.5775 |
  | 0.7335        | 4.0   | 604  | 1.0644          | 0.5861   | 0.5816 |
  | 0.6786        | 5.0   | 755  | 1.0946          | 0.5782   | 0.5769 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  