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marklicata/M365_h2_Text_Processing_and_Summarization

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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M365h2TextProcessingand_Summarization

This model is a fine-tuned version of marklicata/M365_h1_base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0282

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: 5e-05
  • trainbatchsize: 8
  • evalbatchsize: 8
  • seed: 42
  • optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • num_epochs: 3.0

Training results

Training LossEpochStepValidation Loss
0.04691.017710.0380
0.01092.035420.0268
0.00293.053130.0282

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.4.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.1