results

This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on 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 was used as the base model, which can pretty much handle various tasks. Just specialized it with the dataset of 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

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Llama-turkish-lawbot