nhatha2004/Mistral7BInstruct-lora-classifier-test

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Mistral7BInstruct-lora-classifier-test

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 245.375
• —Accuracy: 0.5667
• —F1 Macro: 0.4937
• —F1 Weighted: 0.4645

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: 0.02
• —trainbatchsize: 16
• —evalbatchsize: 16
• —seed: 42
• —gradientaccumulationsteps: 8
• —totaltrainbatch_size: 128
• —optimizer: Use pagedadamw8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 5

Training results

Framework versions

• —PEFT 0.17.1
• —Transformers 4.52.4
• —Pytorch 2.6.0+cu124
• —Datasets 4.1.1
• —Tokenizers 0.21.4