Overview

This model, Adanato/llama3_8b_instruct_qwen25_qwen3_rank_only-qwen25_qwen3_rank_only_cluster_5, is an 8 billion parameter instruction-tuned language model. It is a fine-tuned variant of the robust Meta-Llama-3-8B-Instruct base model, specifically adapted using the qwen25_qwen3_rank_only_cluster_5 dataset.

Key Capabilities

• Instruction Following: Inherits and refines the instruction-following capabilities of the Llama 3 8B Instruct base model.
• Specialized Adaptation: Fine-tuned on a specific dataset, suggesting potential specialization for tasks or data distributions present in qwen25_qwen3_rank_only_cluster_5.
• Context Handling: Supports a context length of 8192 tokens, allowing for processing of moderately long inputs.

Training Details

The model was trained with a learning rate of 1e-05, a total training batch size of 128 (across 4 GPUs with 8 gradient accumulation steps), and a cosine learning rate scheduler with a 0.1 warmup ratio. Training was conducted for 1 epoch using the AdamW_TORCH_FUSED optimizer.

Good for

• Applications requiring a specialized Llama 3 8B Instruct model tailored to the characteristics of the qwen25_qwen3_rank_only_cluster_5 dataset.
• Tasks where the specific fine-tuning data provides an advantage over the general-purpose base model.
• Scenarios benefiting from an 8B parameter model with an 8192-token context window.