gpt2-medium-vaguely-human-dialogue

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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

Framework versions

• Transformers 4.16.1
• Pytorch 1.10.0+cu111
• Tokenizers 0.11.0