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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
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss
34.991 1.0 837 14.8359
12.2881 2.0 1674 9.375
8.5071 3.0 2511 7.2148
7.6031 4.0 3348 6.1758
6.4808 5.0 4185 5.5820
5.8562 6.0 5022 5.0977
5.6094 7.0 5859 4.8203
5.2591 8.0 6696 4.5977
5.0031 9.0 7533 4.4219
4.8837 10.0 8370 4.3281

Framework versions

  • Transformers 4.16.1
  • Pytorch 1.10.0+cu111
  • Tokenizers 0.11.0
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