---
license: mit
tags:
- generated_from_trainer
base_model: law-ai/InLegalBERT
metrics:
- accuracy
- precision
- recall
model-index:
- name: InLegalBERT
  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. -->

# InLegalBERT

This model is a fine-tuned version of [law-ai/InLegalBERT](https://huggingface.co/law-ai/InLegalBERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5527
- Accuracy: 0.7591
- Precision: 0.7598
- Recall: 0.7591
- Precision Macro: 0.6792
- Recall Macro: 0.6780
- Macro Fpr: 0.0228
- Weighted Fpr: 0.0222
- Weighted Specificity: 0.9703
- Macro Specificity: 0.9820
- Weighted Sensitivity: 0.7591
- Macro Sensitivity: 0.6780
- F1 Micro: 0.7591
- F1 Macro: 0.6756
- F1 Weighted: 0.7583

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | Accuracy | Precision | Recall | Precision Macro | Recall Macro | Macro Fpr | Weighted Fpr | Weighted Specificity | Macro Specificity | Weighted Sensitivity | Macro Sensitivity | F1 Micro | F1 Macro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---------------:|:------------:|:---------:|:------------:|:--------------------:|:-----------------:|:--------------------:|:-----------------:|:--------:|:--------:|:-----------:|
| 1.9079        | 1.0   | 643  | 1.2971          | 0.5732   | 0.5257    | 0.5732 | 0.3206          | 0.3555       | 0.0535    | 0.0505       | 0.9314               | 0.9670            | 0.5732               | 0.3555            | 0.5732   | 0.3189   | 0.5343      |
| 1.2081        | 2.0   | 1286 | 0.9146          | 0.7103   | 0.7163    | 0.7103 | 0.6091          | 0.5215       | 0.0287    | 0.0283       | 0.9651               | 0.9784            | 0.7103               | 0.5215            | 0.7103   | 0.5206   | 0.7070      |
| 0.9303        | 3.0   | 1929 | 0.8692          | 0.7405   | 0.7472    | 0.7405 | 0.6654          | 0.5940       | 0.0248    | 0.0244       | 0.9679               | 0.9806            | 0.7405               | 0.5940            | 0.7405   | 0.5993   | 0.7362      |
| 0.4996        | 4.0   | 2572 | 1.1656          | 0.7033   | 0.7270    | 0.7033 | 0.6366          | 0.6241       | 0.0297    | 0.0292       | 0.9651               | 0.9779            | 0.7033               | 0.6241            | 0.7033   | 0.6125   | 0.6959      |
| 0.3592        | 5.0   | 3215 | 1.0837          | 0.7459   | 0.7535    | 0.7459 | 0.6627          | 0.6131       | 0.0241    | 0.0238       | 0.9668               | 0.9808            | 0.7459               | 0.6131            | 0.7459   | 0.6261   | 0.7447      |
| 0.2809        | 6.0   | 3858 | 1.2175          | 0.7545   | 0.7607    | 0.7545 | 0.6758          | 0.6585       | 0.0232    | 0.0227       | 0.9695               | 0.9816            | 0.7545               | 0.6585            | 0.7545   | 0.6599   | 0.7531      |
| 0.1664        | 7.0   | 4501 | 1.3113          | 0.7637   | 0.7645    | 0.7637 | 0.6855          | 0.6886       | 0.0221    | 0.0216       | 0.9717               | 0.9824            | 0.7637               | 0.6886            | 0.7637   | 0.6841   | 0.7631      |
| 0.0733        | 8.0   | 5144 | 1.4751          | 0.7552   | 0.7610    | 0.7552 | 0.6835          | 0.6990       | 0.0231    | 0.0226       | 0.9697               | 0.9817            | 0.7552               | 0.6990            | 0.7552   | 0.6871   | 0.7566      |
| 0.0716        | 9.0   | 5787 | 1.5509          | 0.7637   | 0.7605    | 0.7637 | 0.7018          | 0.7035       | 0.0224    | 0.0216       | 0.9690               | 0.9822            | 0.7637               | 0.7035            | 0.7637   | 0.7006   | 0.7609      |
| 0.0286        | 10.0  | 6430 | 1.5527          | 0.7591   | 0.7598    | 0.7591 | 0.6792          | 0.6780       | 0.0228    | 0.0222       | 0.9703               | 0.9820            | 0.7591               | 0.6780            | 0.7591   | 0.6756   | 0.7583      |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2