---
license: cc-by-sa-4.0
base_model: nlpaueb/legal-bert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: Sidziesama/Legal_NER_Support_Model
  results: []

datasets:
- opennyaiorg/InLegalNER
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# Sidziesama/Legal_NER_Support_Model

This model is a fine-tuned version of [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpaueb/legal-bert-base-uncased) on [opennyaiorg/InLegalNER](https://huggingface.co/datasets/opennyaiorg/InLegalNER).
It achieves the following results on the evaluation set:
- Train Loss: 0.0501
- Validation Loss: 0.0883
- Train Precision: 0.8848
- Train Recall: 0.9160
- Train F1: 0.9001
- Train Accuracy: 0.9757
- Epoch: 4

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2945, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
| 0.3771     | 0.1228          | 0.8400          | 0.8644       | 0.8520   | 0.9655         | 0     |
| 0.1172     | 0.0962          | 0.8715          | 0.9001       | 0.8856   | 0.9725         | 1     |
| 0.0801     | 0.0895          | 0.8805          | 0.9112       | 0.8956   | 0.9745         | 2     |
| 0.0597     | 0.0881          | 0.8840          | 0.9112       | 0.8974   | 0.9751         | 3     |
| 0.0501     | 0.0883          | 0.8848          | 0.9160       | 0.9001   | 0.9757         | 4     |


### Framework versions

- Transformers 4.39.3
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2