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sst-gpt2

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

  • Loss: 0.0218
  • Mse: 0.0218

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
  • train_batch_size: 16
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Mse
0.2144 1.0 534 0.0300 0.0301
0.0251 2.0 1068 0.0249 0.0250
0.0181 3.0 1602 0.0230 0.0230
0.0134 4.0 2136 0.0244 0.0244
0.0096 5.0 2670 0.0228 0.0228
0.0077 6.0 3204 0.0227 0.0227
0.0062 7.0 3738 0.0227 0.0227
0.0052 8.0 4272 0.0229 0.0229
0.0044 9.0 4806 0.0227 0.0226
0.0038 10.0 5340 0.0240 0.0240
0.0034 11.0 5874 0.0221 0.0221
0.0029 12.0 6408 0.0220 0.0220
0.0026 13.0 6942 0.0229 0.0229
0.0024 14.0 7476 0.0217 0.0217
0.002 15.0 8010 0.0225 0.0225
0.0018 16.0 8544 0.0222 0.0222
0.0016 17.0 9078 0.0217 0.0217
0.0015 18.0 9612 0.0218 0.0218
0.0014 19.0 10146 0.0217 0.0217
0.0013 20.0 10680 0.0218 0.0218

Framework versions

  • Transformers 4.37.0
  • Pytorch 1.13.1+cu117
  • Datasets 2.15.0
  • Tokenizers 0.15.2
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Model size
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F32
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Finetuned from

Dataset used to train kennethge123/sst-gpt2