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-V3
  
  This model is a fine-tuned version of [alexaapo/greek_legal_bert_v2](https://huggingface.co/alexaapo/greek_legal_bert_v2) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0907
  - Precision: 0.9023
  - Recall: 0.9265
  - F1: 0.9142
  - Accuracy: 0.9828
  
  ## 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   | 0.0661          | 0.8895    | 0.9229 | 0.9059 | 0.9813   |
  | No log        | 2.38  | 50   | 0.0820          | 0.9091    | 0.9319 | 0.9204 | 0.9838   |
  | No log        | 3.57  | 75   | 0.0791          | 0.8924    | 0.9211 | 0.9065 | 0.9825   |
  | No log        | 4.76  | 100  | 0.0824          | 0.8950    | 0.9319 | 0.9131 | 0.9841   |
  | No log        | 5.95  | 125  | 0.0820          | 0.8830    | 0.9194 | 0.9008 | 0.9812   |
  | No log        | 7.14  | 150  | 0.0862          | 0.9059    | 0.9319 | 0.9187 | 0.9817   |
  | No log        | 8.33  | 175  | 0.0915          | 0.9021    | 0.9247 | 0.9133 | 0.9826   |
  | No log        | 9.52  | 200  | 0.0905          | 0.9023    | 0.9265 | 0.9142 | 0.9828   |
  
  
  ### Framework versions
  
  - Transformers 4.23.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.2
  - Tokenizers 0.13.1