---
license: llama2
tags:
- llama-factory
- legal
base_model: sudipto-ducs/InLegalLLaMA
model-index:
- name: sudipto-ducs/InLegalLLaMA-Instruct
  results: []
language:
- en
pipeline_tag: table-question-answering
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# InLegalLLaMA-Instruct

This model is a fine-tuned version of [sudipto-ducs/InLegalLLaMA](https://huggingface.co/sudipto-ducs/InLegalLLaMA) on the legalkg_dataset_prompts, the legal_semantic_segmentation and the lima datasets.

## 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: 3e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- PEFT 0.10.0
- Transformers 4.39.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2