File size: 1,834 Bytes
3a898ce 9a5772b 3a898ce ea44731 9a5772b 3a898ce bc8ae33 3a898ce 88ac4d8 3a898ce bc8ae33 3a898ce ea44731 3a898ce ea44731 3a898ce ea44731 3a898ce ea44731 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
---
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: []
---
<!-- 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. -->
# gpt2-context_generator
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2/) on [Non-Residual-Prompting/C2Gen](https://huggingface.co/datasets/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](https://arxiv.org/abs/1911.03705) 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](https://aclanthology.org/2022.acl-long.471) 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 |