readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: mbert-targin-final
    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. -->
  
  # mbert-targin-final
  
  This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9847
  - Accuracy: 0.7025
  - Precision: 0.6490
  - Recall: 0.6487
  - F1: 0.6489
  
  ## 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: 1e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - 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 | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | No log        | 1.0   | 296  | 0.5774          | 0.7091   | 0.6506    | 0.6378 | 0.6426 |
  | 0.5912        | 2.0   | 592  | 0.5316          | 0.7376   | 0.6880    | 0.6767 | 0.6814 |
  | 0.5912        | 3.0   | 888  | 0.5511          | 0.7253   | 0.6692    | 0.6293 | 0.6378 |
  | 0.4844        | 4.0   | 1184 | 0.6262          | 0.6835   | 0.6622    | 0.6884 | 0.6613 |
  | 0.4844        | 5.0   | 1480 | 0.6320          | 0.7006   | 0.6574    | 0.6701 | 0.6616 |
  | 0.3861        | 6.0   | 1776 | 0.6983          | 0.7148   | 0.6632    | 0.6620 | 0.6626 |
  | 0.2773        | 7.0   | 2072 | 0.8109          | 0.7110   | 0.6630    | 0.6689 | 0.6655 |
  | 0.2773        | 8.0   | 2368 | 0.8948          | 0.7072   | 0.6525    | 0.6487 | 0.6504 |
  | 0.2068        | 9.0   | 2664 | 0.9693          | 0.7072   | 0.6519    | 0.6469 | 0.6492 |
  | 0.2068        | 10.0  | 2960 | 0.9847          | 0.7025   | 0.6490    | 0.6487 | 0.6489 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  