---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: Sidziesama/Legal_NER_Support_Model_distilledbert
  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_distilledbert

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on 
[opennyaiorg/InLegalNER](https://huggingface.co/datasets/opennyaiorg/InLegalNER).
It achieves the following results on the evaluation set:
- Train Loss: 0.0582
- Validation Loss: 0.0980
- Train Precision: 0.7952
- Train Recall: 0.8552
- Train F1: 0.8241
- Train Accuracy: 0.9716
- 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': 3435, '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 |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
| 0.4207     | 0.1608          | 0.6623          | 0.7498       | 0.7034   | 0.9557         | 0     |
| 0.1304     | 0.1118          | 0.7580          | 0.8116       | 0.7839   | 0.9668         | 1     |
| 0.0891     | 0.1012          | 0.7698          | 0.8525       | 0.8090   | 0.9701         | 2     |
| 0.0699     | 0.0976          | 0.7933          | 0.8507       | 0.8210   | 0.9713         | 3     |
| 0.0582     | 0.0980          | 0.7952          | 0.8552       | 0.8241   | 0.9716         | 4     |


### Framework versions

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