ngocnamk3er/rag-llm-qwen2.5-7b-lora-24DEC

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rag-llm-qwen2.5-7b-lora-24DEC

This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 0.1689
• —Em: 0.0
• —F1: 0.9422
• —Rougel: 0.9497
• —Refusal Accuracy: 1.0

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 0.0002
• —trainbatchsize: 1
• —evalbatchsize: 1
• —seed: 42
• —gradientaccumulationsteps: 8
• —totaltrainbatch_size: 8
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 3

Training results

Framework versions

• —PEFT 0.10.0
• —Transformers 4.41.2
• —Pytorch 2.9.1+cu128
• —Datasets 2.18.0
• —Tokenizers 0.19.1