readme: ---
  license: cc-by-nc-3.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: finetuning-hs-model-bert-multilingual
    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. -->
  
  # finetuning-hs-model-bert-multilingual
  
  This model is a fine-tuned version of [QCRI/bert-base-multilingual-cased-pos-english](https://huggingface.co/QCRI/bert-base-multilingual-cased-pos-english) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3158
  - Accuracy: 0.9575
  - F1: 0.0
  - Precision: 0.0
  - Recall: 0.0
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  