Zephyr-7B-SFT-Full
| Property | Value |
|---|---|
| Parameter Count | 7.24B |
| License | Apache 2.0 |
| Base Model | Mistral-7B-v0.1 |
| Training Dataset | UltraChat 200k |
| Precision | BF16 |
What is zephyr-7b-sft-full?
Zephyr-7B-SFT-Full is a sophisticated language model that builds upon the powerful Mistral-7B architecture. This model represents a significant advancement in conversational AI, having been fine-tuned on the comprehensive UltraChat 200k dataset using Supervised Fine-Tuning (SFT) techniques.
Implementation Details
The model was trained using a distributed multi-GPU setup across 8 devices, implementing the Adam optimizer with carefully tuned hyperparameters (betas=0.9,0.999, epsilon=1e-08). The training process utilized a cosine learning rate scheduler with a 0.1 warmup ratio and achieved a final validation loss of 0.9353.
- Learning rate: 2e-05
- Total batch size: 128 (16 per GPU)
- Training duration: 1 epoch
- Evaluation batch size: 64
Core Capabilities
- Advanced text generation and conversational abilities
- Optimized for production deployment with text-generation-inference support
- Compatible with TensorBoard for monitoring and visualization
- Equipped with safety-focused implementations through Safetensors
Frequently Asked Questions
Q: What makes this model unique?
The model combines the powerful Mistral-7B architecture with supervised fine-tuning on high-quality conversational data, achieving a remarkable training loss of 0.9075 and validation loss of 0.9353. Its implementation using BF16 precision offers an optimal balance between performance and resource efficiency.
Q: What are the recommended use cases?
The model is particularly well-suited for conversational AI applications, text generation tasks, and applications requiring sophisticated language understanding and generation capabilities. Its integration with text-generation-inference makes it ideal for production deployments.
