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Model: sudipto-ducs/InLegalLLaMA-Instruct
Source: Original Platform

README.md

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+---
+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
+should probably proofread and complete it, then remove this comment. -->
+
+# 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