readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bert-base-multilingual-cased-finetuned-ijelid
    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-cased-finetuned-ijelid
  
  This model was trained from scratch on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5701
  - Precision: 0.9255
  - Recall: 0.9206
  - F1: 0.9229
  - Accuracy: 0.9449
  
  ## 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: 3e-05
  - train_batch_size: 256
  - eval_batch_size: 128
  - 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 | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 25   | 0.5654          | 0.9300    | 0.9143 | 0.9219 | 0.9443   |
  | No log        | 2.0   | 50   | 0.5853          | 0.9272    | 0.9162 | 0.9214 | 0.9437   |
  | No log        | 3.0   | 75   | 0.5760          | 0.9275    | 0.9199 | 0.9235 | 0.9445   |
  | No log        | 4.0   | 100  | 0.5733          | 0.9254    | 0.9209 | 0.9230 | 0.9445   |
  | No log        | 5.0   | 125  | 0.5701          | 0.9255    | 0.9206 | 0.9229 | 0.9449   |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu102
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  