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greatakela/multilabel_classification

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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Model Card

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multilabel_classification

This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.1275
  • —F1 Micro: 0.8546
  • —F1 Macro: 0.5865
  • —Accuracy: 0.9780

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: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_ratio: 0.1
  • —num_epochs: 3

Training results

Training LossEpochStepValidation LossF1 MicroF1 MacroAccuracy
No log1.02550.29390.82820.56960.9604
0.75872.05100.19650.85460.58650.9780
0.75873.07650.12750.85460.58650.9780

Framework versions

  • —PEFT 0.8.2
  • —Transformers 4.37.2
  • —Pytorch 2.2.0+cu121
  • —Datasets 2.17.0
  • —Tokenizers 0.15.2