readme: ---
  tags:
  - name entity recognition
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: finetune-bert-base-multilingual-cased-ner-hrl
    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. -->
  
  # finetune-bert-base-multilingual-cased-ner-hrl
  
  This model is a fine-tuned version of [Davlan/bert-base-multilingual-cased-ner-hrl](https://huggingface.co/Davlan/bert-base-multilingual-cased-ner-hrl) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0332
  - Precision: 0.9543
  - Recall: 0.9535
  - F1: 0.9539
  - Accuracy: 0.9554
  
  ## 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: 12
  - eval_batch_size: 12
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.3333333333333333
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.0436        | 1.0   | 899  | 0.0407          | 0.9079    | 0.9206 | 0.9142 | 0.9255   |
  | 0.0265        | 2.0   | 1798 | 0.0271          | 0.9391    | 0.9383 | 0.9387 | 0.9420   |
  | 0.01          | 3.0   | 2697 | 0.0291          | 0.9544    | 0.9473 | 0.9509 | 0.9433   |
  | 0.0084        | 4.0   | 3596 | 0.0326          | 0.9601    | 0.9515 | 0.9558 | 0.9518   |
  | 0.003         | 5.0   | 4495 | 0.0332          | 0.9543    | 0.9535 | 0.9539 | 0.9554   |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.10.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  