---
library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-3B-Instruct
tags:
- generated_from_trainer
model-index:
- name: results
  results: []
datasets:
- Renicames/turkish-law-chatbot
language:
- tr
---

<!-- 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. -->

# results

This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct)
on [Renicames/turkish-law-chatbot](https://huggingface.co/Renicames/turkish-law-chatbot) dataset, designed to generate responses
based on Turkish legal questions and answers.

## Model description

This model is fine-tuned to imporove its ability to generate responses for a Turkish law chatbot.
[meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) was
used as the base model, which can pretty much handle various tasks. Just specialized it with 
the dataset of [Renicames/turkish-law-chatbot](https://huggingface.co/Renicames/turkish-law-chatbot).

## Intended uses & limitations

### Intended uses
- This model can be deployed in applications aimed at providing legal information or answering legal questions in Turkish.
- Useful for generating legal text, such as explanations of laws or providing examples of legal processes in Turkish.

### Limitaions
- While the model has been fine-tuned on the Turkish legal domain, it may still lack the depth and specificity required for
  complex legal inquiries. It might not be suitable for professional legal advice.
- As with any AI model, it may reflect biases found in the training data, so it should be used with caution in critical applications.
- This model is focused on the Turkish language, so it may not perform well in other languages or mixed-language queries.

## Training and evaluation data

### Training data details:
- Source: Renicames/turkish-law-chatbot dataset
- Languages: Turkish
- Content: Legal questions and answers
- Size: The dataset consists of several thousand question-answer pairs related to Turkish law.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 3

### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0