fake-gpt-2-17m

This model is a GPTJ (with 17,637,632 parameters) trained from scratch on a synthetic dataset (1gb of documents created in 4 fake languages, each with a formal and informal writing style) for 1 epoch.

It achieves the following results on the evaluation set:

• Loss: 3.5592

Intended uses & limitations

This model is to be used as a base model for fine-tuning any language/task to probe the effectiveness of both pre-training on an algorithmically generated corpus and effectiveness of extremely small language models (SLMs?). It can only generate text based on its training data (which will be uploaded as a huggingface dataset soon).

Training and evaluation data

More information needed

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.001
• batch_size 64
• seed: 42
• optimizer: Adam
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Framework versions

• Transformers 4.22.1
• Pytorch 1.12.0
• Datasets 2.3.2
• Tokenizers 0.12.1