Model Overview

The dtorres-zAgile/llama2-7b-zc-domain-misti is a 7 billion parameter language model, fine-tuned from the meta-llama/Llama-2-7b-chat-hf base model. This adaptation focuses on a specific, currently unspecified, domain, aiming to enhance performance for targeted applications.

Training Details

The model underwent a fine-tuning process with the following key hyperparameters:

• Learning Rate: 2e-05
• Batch Size: 8 (for both training and evaluation)
• Optimizer: Adam with default betas and epsilon
• Training Steps: 20

During training, the model achieved a final training loss of 1.7949 and a validation loss of 1.9632. The training utilized Transformers 4.34.1, Pytorch 2.1.0, Datasets 2.14.6, and Tokenizers 0.14.1.

Intended Use

This model is designed for use cases within the specific domain it was fine-tuned on. Developers should consider its specialized nature when integrating it into applications, as its performance is optimized for this particular context rather than general-purpose tasks.