readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: greek_legal_bert_v2-finetuned-ner-V3
    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. -->
  
  # greek_legal_bert_v2-finetuned-ner-V4
  
  This model is a fine-tuned version of [amichailidis/greek_legal_bert_v2-finetuned-ner](https://huggingface.co/amichailidis/greek_legal_bert_v2-finetuned-ner) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0659
  - Precision: 0.9033
  - Recall: 0.9373
  - F1: 0.9200
  - Accuracy: 0.9845
  
  ## 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
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.19  | 25   | 0.1246          | 0.8264    | 0.8190 | 0.8227 | 0.9680   |
  | No log        | 2.38  | 50   | 0.0729          | 0.8716    | 0.9247 | 0.8974 | 0.9809   |
  | No log        | 3.57  | 75   | 0.0553          | 0.8978    | 0.9444 | 0.9205 | 0.9851   |
  | No log        | 4.76  | 100  | 0.0591          | 0.8990    | 0.9409 | 0.9194 | 0.9852   |
  | No log        | 5.95  | 125  | 0.0598          | 0.9017    | 0.9373 | 0.9192 | 0.9849   |
  | No log        | 7.14  | 150  | 0.0628          | 0.9064    | 0.9373 | 0.9216 | 0.9842   |
  | No log        | 8.33  | 175  | 0.0636          | 0.9031    | 0.9355 | 0.9190 | 0.9843   |
  | No log        | 9.52  | 200  | 0.0659          | 0.9033    | 0.9373 | 0.9200 | 0.9845   |
  
  
  ### Framework versions
  
  - Transformers 4.23.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.2
  - Tokenizers 0.13.1
  