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NasimB/gpt2-concat-cbt-mod-formatting-iorder-rarity-all-4k

sourceHugging Facemitupdated 3y agoView on Hugging Face
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Model Card

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gpt2-concat-cbt-mod-formatting-iorder-rarity-all-4k

This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:

  • —Loss: 4.3158

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: 0.0005
  • —trainbatchsize: 64
  • —evalbatchsize: 64
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 1000
  • —num_epochs: 6
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation Loss
6.69620.295005.6482
5.33520.5910005.2168
4.99630.8815004.9671
4.71471.1720004.8164
4.55081.4625004.6852
4.45031.7630004.5766
4.32332.0535004.4995
4.12392.3440004.4513
4.09342.6345004.3905
4.06452.9350004.3376
3.85383.2255004.3338
3.79373.5160004.3034
3.7813.865004.2718
3.68214.170004.2702
3.50824.3975004.2633
3.50784.6880004.2471
3.49364.9785004.2346
3.345.2790004.2492
3.31455.5695004.2471
3.3155.85100004.2463

Framework versions

  • —Transformers 4.26.1
  • —Pytorch 1.11.0+cu113
  • —Datasets 2.13.0
  • —Tokenizers 0.13.3