---
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: 0.1041
- Precision: 0.7985
- Recall: 0.8638
- F1: 0.8298
- Accuracy: 0.9697

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4662        | 1.0   | 917  | 0.1419          | 0.6784    | 0.7845 | 0.7276 | 0.9533   |
| 0.1146        | 2.0   | 1834 | 0.1084          | 0.7529    | 0.8508 | 0.7988 | 0.9623   |
| 0.0711        | 3.0   | 2751 | 0.1015          | 0.8031    | 0.8627 | 0.8318 | 0.9705   |
| 0.0546        | 4.0   | 3668 | 0.1041          | 0.7985    | 0.8638 | 0.8298 | 0.9697   |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0