readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: fine-tuned-ai-ss-hs-01
    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. -->
  
  # fine-tuned-ai-ss-hs-01
  
  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:
  - AUC: 0.88609
  - Precision: 0.8514
  - Accuracy: 0.8101
  - F1: 0.7875
  - Recall: 0.7326
  
  ## 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: 1.1207606211860595e-05
  - train_batch_size: 16
  - eval_batch_size: 4
  - seed: 2
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | No log        | 1.0   | 357  | 1.0285          | 0.6955   | 0.5657 | 0.8987    | 0.4128 |
  | 0.5857        | 2.0   | 714  | 1.0350          | 0.7207   | 0.6296 | 0.8673    | 0.4942 |
  | 0.51          | 3.0   | 1071 | 0.7467          | 0.8156   | 0.7975 | 0.8442    | 0.7558 |
  | 0.51          | 4.0   | 1428 | 0.8376          | 0.8101   | 0.7875 | 0.8514    | 0.7326 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Tokenizers 0.12.1
  