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p-tuning-gpt2-large-with-sst2
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metadata
license: mit
base_model: gpt2
tags:
  - generated_from_trainer
metrics:
  - accuracy
library_name: peft
model-index:
  - name: p-tuning-gpt2-large-with-sst2
    results: []

p-tuning-gpt2-large-with-sst2

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

  • Loss: 0.3065
  • Accuracy: 0.8968

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: 0.0001
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.4485 1.0 4210 0.3556 0.8406
0.2677 2.0 8420 0.3760 0.8693
0.2717 3.0 12630 0.3264 0.8727
0.3687 4.0 16840 0.3410 0.8807
0.3483 5.0 21050 0.3075 0.8865
0.2969 6.0 25260 0.3315 0.8888
0.3577 7.0 29470 0.2875 0.8853
0.4036 8.0 33680 0.3143 0.8899
0.404 9.0 37890 0.2858 0.8911
0.2797 10.0 42100 0.3035 0.8876
0.3328 11.0 46310 0.3168 0.8876
0.2345 12.0 50520 0.3063 0.8933
0.3154 13.0 54730 0.2972 0.8911
0.2937 14.0 58940 0.2994 0.8933
0.2123 15.0 63150 0.2938 0.8899
0.295 16.0 67360 0.3087 0.8945
0.1924 17.0 71570 0.3031 0.8933
0.2415 18.0 75780 0.3067 0.8979
0.1876 19.0 79990 0.3080 0.8979
0.3891 20.0 84200 0.3065 0.8968

Framework versions

  • PEFT 0.7.1
  • Transformers 4.40.1
  • Pytorch 2.5.0
  • Datasets 3.0.1
  • Tokenizers 0.19.1