CoolFace
Modelpublic

pszemraj/gpt2-medium-vaguely-human-dialogue

sourceHugging Facemitupdated 9mo agoView on Hugging Face
0likes51downloads
Model Card

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

pszemraj/gpt2-medium-vaguely-human-dialogue

This model is a fine-tuned version of gpt2-medium on a parsed version of Wizard of Wikipedia. Because the batch size was so large, it learned a general understanding of words that makes sense together but does not specifically respond to anything - sort of like an alien learning to imitate human words to convince others that it is human.

It achieves the following results on the evaluation set:

  • —Loss: 4.3281

Model description

  • —a decent example of what happens when your batch size is too large and the global optima does not reflect specific prompts / use cases.

Intended uses & limitations

  • —there are no intended uses

Training and evaluation data

  • —a parsed version of the wizard of Wikipedia dataset

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • —learning_rate: 2e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 32
  • —seed: 42
  • —distributed_type: multi-GPU
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 64
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_ratio: 0.05
  • —num_epochs: 10

Training results

Training LossEpochStepValidation Loss
34.9911.083714.8359
12.28812.016749.375
8.50713.025117.2148
7.60314.033486.1758
6.48085.041855.5820
5.85626.050225.0977
5.60947.058594.8203
5.25918.066964.5977
5.00319.075334.4219
4.883710.083704.3281

Framework versions

  • —Transformers 4.16.1
  • —Pytorch 1.10.0+cu111
  • —Tokenizers 0.11.0