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NasimB/gpt2-concat-finetune-cl-mod-datasets-rarity1

sourceHugging Faceupdated 3y agoView on Hugging Face
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Model Card

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gpt2-concat-finetune-cl-mod-datasets-rarity1

This model was trained from scratch on the generator dataset. It achieves the following results on the evaluation set:

  • —Loss: 2.6666

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: 5
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation Loss
3.83060.35004.5102
3.94430.5910004.5278
4.0390.8915004.4641
3.88591.1820004.4729
3.85191.4825004.4332
3.86221.7830004.3895
3.7652.0735004.4085
3.54152.3740004.4023
3.56312.6645004.3729
3.5592.9650004.3403
3.23243.2655004.4037
3.20113.5560004.3997
3.18983.8565004.3837
3.04724.1470004.4190
2.90364.4475004.4273
2.89854.7480004.4269

Framework versions

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