Parameter	Value
Base model	mistralai/Mistral-7B-Instruct-v0.3
Method	LoRA + QLoRA (4-bit quantization)
LoRA rank (r)	16
LoRA alpha	16
Target modules	q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
Trainable parameters	~1% of total
Training epochs	3
Final training loss	1.9318
Final validation loss	1.8930
Validation loss improvement	14.5% over epoch 1
Framework	Unsloth + PEFT + TRL
Hardware	Google Colab T4 GPU

📊 Training Results

Epoch	Training Loss	Validation Loss
1	2.0929	2.2116
2	2.0924	2.0939
3	1.9318	1.8930

Consistent decrease in both training and validation loss across all epochs, with validation loss dropping below training loss at epoch 3 — indicating good generalization on the small domain-specific dataset.

📄 License

This model adapter is released under the Apache 2.0 license, consistent with the base Mistral-7B model license.

udishaduttachowdhury/mistral-7b-iot-anomaly-detection-lora

Mistral-7B IoT Anomaly Detection — LoRA Adapter

🏭 Use Case

🔧 Training Details

📊 Training Results

📄 License

udishaduttachowdhury/
mistral-7b-iot-anomaly-detection-lora