---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: alexaapo/greek_legal_bert_v2
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
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# 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