---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: legal_ai_India_ner_results
  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. -->

# legal_ai_India_ner_results

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0989
- Precision: 0.8007
- Recall: 0.8602
- F1: 0.8294
- Accuracy: 0.9700

## 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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4454        | 1.0   | 917  | 0.1342          | 0.6886    | 0.7867 | 0.7344 | 0.9554   |
| 0.1136        | 2.0   | 1834 | 0.1004          | 0.7818    | 0.8418 | 0.8107 | 0.9665   |
| 0.0712        | 3.0   | 2751 | 0.0973          | 0.7990    | 0.8551 | 0.8261 | 0.9705   |
| 0.0535        | 4.0   | 3668 | 0.0989          | 0.8007    | 0.8602 | 0.8294 | 0.9700   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0