artificialguybr/QWEN-2-1.5B-Synthia-I

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Qwen2-1.5B Fine-tuned on Synthia v1.5-I

This model is a fine-tuned version of Qwen/Qwen2-1.5B on the Synthia v1.5-I dataset, which contains over 20.7k instruction-following examples.

Model Description

Qwen2-1.5B is part of the latest Qwen2 series of large language models. The base model brings significant improvements in:

• —Language understanding and generation
• —Structured data processing
• —Support for multiple languages
• —Long context handling

🌐 Website

You can find more of my models, projects, and information on my official website:

• —[artificialguy.com](https://artificialguy.com/)

🚀 Prompt Hub

Need high-quality prompts for image models and LLMs? Explore [findgoodprompt.com](https://findgoodprompt.com).

💖 Support My Work

If you find this model useful, please consider supporting my work. It helps me cover server costs and dedicate more time to new open-source projects.

• —Patreon: Support on Patreon
• —Ko-fi: Buy me a Ko-fi
• —Buy Me a Coffee: Buy me a Coffee This fine-tuned version enhances the base model's instruction-following capabilities through training on the Synthia v1.5-I dataset.

Model Architecture

• —Type: Causal Language Model
• —Parameters: 1.5B
• —Training Framework: Transformers 4.45.0.dev0

Intended Uses & Limitations

This model is intended for:

• —Instruction following and task completion
• —Text generation and completion
• —Conversational AI applications

The model inherits the capabilities of the base Qwen2-1.5B model, while being specifically tuned for instruction following.

Training Procedure

Training Data

The model was fine-tuned on the Synthia v1.5-I dataset containing 20.7k instruction-following examples.

Training Hyperparameters

The following hyperparameters were used during training:

• —Learning rate: 1e-05
• —Train batch size: 5
• —Eval batch size: 5
• —Seed: 42
• —Gradient accumulation steps: 8
• —Total train batch size: 40
• —Optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —LR scheduler type: cosine
• —LR scheduler warmup steps: 100
• —Number of epochs: 3
• —Sequence length: 4096
• —Sample packing: enabled
• —Pad to sequence length: enabled

Framework Versions

• —Transformers 4.45.0.dev0
• —Pytorch 2.3.1+cu121
• —Datasets 2.21.0
• —Tokenizers 0.19.1

<details><summary>See axolotl config</summary>

axolotl version: 0.4.1

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Explore More

Discover more of my models, projects, and practical AI resources:

• —AI tools directory: JustGoodAI — a curated directory of useful AI tools.

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