metadata

language:
  - en
license: cc-by-sa-4.0
tags:
  - generated_from_trainer
  - text-generation-inference
datasets:
  - Non-Residual-Prompting/C2Gen
pipeline_tag: text-generation
base_model: gpt2
model-index:
  - name: gpt2-commongen-finetuned
    results: []

gpt2-context_generator

This model is a fine-tuned version of gpt2 on Non-Residual-Prompting/C2Gen dataset.

Model description

More information needed

Intended uses & limitations

Check config.json for prompt template and sampling strategy.

Dataset Summary

CommonGen Lin et al., 2020 is a dataset for the constrained text generation task of word inclusion. But the task does not allow to include context. Therefore, to complement CommonGen, we provide an extended test set C2Gen Carlsson et al., 2022 where an additional context is provided for each set of target words. The task is therefore reformulated to both generate commonsensical text which include the given words, and also have the generated text adhere to the given context.

Training procedure

Causal Language Modelling

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 9e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.2
num_epochs: 8

Framework versions

Transformers 4.27.3
Pytorch 1.13.1+cu116
Datasets 2.13.1
Tokenizers 0.13.2