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uplimit-project-3-gpt2-large

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

  • Loss: 3.5296

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: 0.001
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss
1.8474 0.4 800 2.7175
1.8784 0.8 1600 2.6618
1.6307 1.2 2400 2.7737
2.0121 1.61 3200 2.6673
2.033 2.01 4000 2.7799
1.8416 2.41 4800 2.8229
1.7133 2.81 5600 2.7827
1.681 3.21 6400 2.9556
1.5638 3.61 7200 2.9581
1.3838 4.02 8000 2.9749
1.2711 4.42 8800 2.9982
1.2488 4.82 9600 2.9858
0.9192 5.22 10400 3.1093
0.914 5.62 11200 3.1497
0.6613 6.02 12000 3.1170
0.6696 6.43 12800 3.1780
0.8281 6.83 13600 3.1630
0.3944 7.23 14400 3.3688
0.4512 7.63 15200 3.3493
0.313 8.03 16000 3.4182
0.3008 8.43 16800 3.4404
0.3054 8.84 17600 3.4577
0.2112 9.24 18400 3.5108
0.2435 9.64 19200 3.5296

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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