kisejin's picture
p-tuning-t2t-gpt2-large-with-sst2
ed83372 verified
metadata
license: mit
base_model: gpt2
tags:
  - generated_from_trainer
metrics:
  - accuracy
library_name: peft
model-index:
  - name: p-tuning-t2t-gpt2-large-with-sst2
    results: []

p-tuning-t2t-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: 0.4929
  • Accuracy: 0.7741

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
0.6984 1.0 4210 0.7020 0.5138
0.6766 2.0 8420 0.6971 0.5138
0.5377 3.0 12630 0.5625 0.7087
0.5375 4.0 16840 0.5481 0.7282
0.5209 5.0 21050 0.5278 0.7420
0.5235 6.0 25260 0.5357 0.7374
0.5311 7.0 29470 0.5342 0.7294
0.5545 8.0 33680 0.5135 0.7511
0.5406 9.0 37890 0.5138 0.7397
0.523 10.0 42100 0.5192 0.7580
0.5248 11.0 46310 0.4997 0.7706
0.559 12.0 50520 0.5063 0.7649
0.582 13.0 54730 0.4958 0.7741
0.4796 14.0 58940 0.4981 0.7706
0.4173 15.0 63150 0.4911 0.7626
0.4449 16.0 67360 0.4932 0.7718
0.4697 17.0 71570 0.4917 0.7741
0.3779 18.0 75780 0.4931 0.7729
0.449 19.0 79990 0.4929 0.7729
0.4938 20.0 84200 0.4929 0.7741

Framework versions

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