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NasimB/gpt2-concat-guten-rarity-no-cut-corrected

sourceHugging Facemitupdated 3y agoView on Hugging Face
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Model Card

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gpt2-concat-guten-rarity-no-cut-corrected

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

  • —Loss: 4.3120

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
6.70390.295005.6444
5.34770.5810005.1977
4.98770.8715004.9542
4.71471.1620004.8034
4.55651.4625004.6723
4.45031.7530004.5667
4.32892.0435004.4930
4.13052.3340004.4433
4.09912.6245004.3879
4.06292.9150004.3392
3.86483.255004.3323
3.80053.4960004.2991
3.78183.7965004.2701
3.69984.0870004.2639
3.51134.3775004.2592
3.51134.6680004.2454
3.50084.9585004.2317
3.34695.2490004.2439
3.31885.5395004.2429
3.31685.82100004.2418

Framework versions

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