File size: 2,230 Bytes
a8bf51b 4c9aef0 a8bf51b 54d5c73 a8bf51b cde5bc1 a8bf51b 2037df2 a8bf51b 7359850 a8bf51b 7359850 a8bf51b 2037df2 a8bf51b 2037df2 a8bf51b 7359850 a8bf51b 7359850 463634f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
library_name: transformers
license: cc-by-sa-4.0
base_model: nlpaueb/legal-bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: legal_ai_India_ner_results
results: []
datasets:
- opennyaiorg/InLegalNER
---
<!-- 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 [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpaueb/legal-bert-base-uncased) on the opennyaiorg/InLegalNER dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1057
- Precision: 0.8370
- Recall: 0.8742
- F1: 0.8552
- Accuracy: 0.9741
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4633 | 1.0 | 917 | 0.1226 | 0.7624 | 0.8040 | 0.7827 | 0.9642 |
| 0.1039 | 2.0 | 1834 | 0.1077 | 0.7996 | 0.8583 | 0.8279 | 0.9702 |
| 0.0686 | 3.0 | 2751 | 0.1021 | 0.8054 | 0.8695 | 0.8362 | 0.9714 |
| 0.048 | 4.0 | 3668 | 0.1084 | 0.8309 | 0.8706 | 0.8503 | 0.9732 |
| 0.0368 | 5.0 | 4585 | 0.1057 | 0.8370 | 0.8742 | 0.8552 | 0.9741 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
|