CoolFace
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mo22zy/LLM-fineTune-LLaMAFactory-UnSloth

sourceHugging Faceapache-2.0updated 14d agoView on Hugging Face
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Model Card

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LLM-fineTune-LLaMAFactory-UnSloth

This model is a fine-tuned version of Qwen/Qwen2.5-0.5B-Instruct on the newsfinetunetrain dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5046

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: 0.0001
  • trainbatchsize: 1
  • evalbatchsize: 1
  • seed: 42
  • gradientaccumulationsteps: 4
  • totaltrainbatch_size: 4
  • optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lrschedulertype: cosine
  • lrschedulerwarmup_steps: 0.1
  • num_epochs: 3.0
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation Loss
0.67510.15591000.6013
0.77270.31192000.5871
0.64160.46783000.5594
0.66860.62384000.5424
0.59990.77975000.5319
0.54030.93576000.5232
0.41611.09047000.5130
0.44901.24648000.5075
0.46941.40239000.4965
0.40711.558310000.4871
0.42851.714211000.4959
0.57571.870212000.5070
0.28102.025013000.5236
0.35072.180914000.5188
0.27872.336815000.5214
0.36362.492816000.5142
0.33442.648717000.5073
0.32012.804718000.5123
0.28662.960619000.4967
0.27673.019260.5046

Framework versions

  • PEFT 0.18.1
  • Transformers 5.8.0
  • Pytorch 2.11.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2