Model Overview

This model, rbelanec/train_sst2_42_1773765558, is a fine-tuned version of the meta-llama/Llama-3.2-1B-Instruct base model, featuring 1 billion parameters. It has been specifically adapted for sentiment analysis by training on the SST-2 dataset.

Key Capabilities

• Sentiment Classification: Optimized for determining the sentiment of text inputs.
• Performance: Achieved a validation loss of 0.1337 on the evaluation set, demonstrating its effectiveness in sentiment analysis.
• Training Details: Trained with a learning rate of 5e-05 over 5 epochs, utilizing an AdamW optimizer and a cosine learning rate scheduler.

Intended Use Cases

This model is particularly well-suited for applications requiring:

• Automated Sentiment Analysis: Classifying customer reviews, social media posts, or feedback.
• Text Understanding: Gaining insights into the emotional tone of written content.

Limitations

As a specialized model, its performance outside of sentiment analysis tasks may be limited. Further details on specific limitations and broader intended uses are not provided in the original model card.