Legal Ner Model
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.1039 Model Preparation Time: 0.0049 Accuracy: 0.9740 Precision: 0.9520...
Model source
- Kind
- Other
- File size
- 473 MB
- Base model
- roberta-base
- Version
- vRevision 7ad520c
- Updated
- Oct 4, 2026
- Publisher
- @ssanskar9
- Downloads
- 27
- Source
- Hugging Face
Source description
legal_ner_model
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1039
- Model Preparation Time: 0.0049
- Accuracy: 0.9740
- Precision: 0.9520
- Recall: 0.9430
- F1: 0.9475
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|---|
| 0.1464 | 1.0 | 1375 | 0.1224 | 0.0049 | 0.9647 | 0.9364 | 0.9204 | 0.9284 |
| 0.0969 | 2.0 | 2750 | 0.1027 | 0.0049 | 0.9723 | 0.9523 | 0.9355 | 0.9438 |
| 0.0814 | 3.0 | 4125 | 0.1039 | 0.0049 | 0.9740 | 0.9520 | 0.9430 | 0.9475 |
Framework versions
- Transformers 4.55.4
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.21.4
Sources
1 source
Sources
1 sourceVerified Oct 4
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
3 excerpts
Source excerpts
3 excerpts--- library_name: transformers license: mit base_model: roberta-base tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: legal_ner_model 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_ner_model This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1039 - Model Preparation Time: 0.0049 - Accuracy: 0.9740 - Precision: 0.9520 - Recall: 0.9430 - F1: 0.9475 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|:---------:|:------:|:------:| | 0.1464 | 1.0 | 1375 | 0.1224 | 0.0049 | 0.9647 | 0.9364 | 0.9204 | 0.9284 | | 0.0969 | 2.0 | 2750 | 0.1027 | 0.0049 | 0.9723 | 0.9523 | 0.9355 | 0.9438 | | 0.0814 | 3.0 | 4125 | 0.1039 | 0.0049 | 0.9740 | 0.9520 | 0.9430 | 0.9475 | ### Framework versions - Transformers 4.55.4 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.21.4
Source context: 27 downloads · 1 likes · Pipeline token-classification · Library transformers · Repo ssanskar9/legal_ner_model
Source context: 26 downloads · 0 likes · Pipeline token-classification · Library transformers · Repo ssanskar9/legal_ner_model
