Text generation model for generating suitable style cues given the main idea for a prompt.It is performing tasks to fine-tune a GPT-2 language model for text generation using a custom dataset. Dataset is collected and trained by students of College of Engineering Guindy.

Athiraj V S
Siva Vignesh S
Someshwar J

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0001
train_batch_size: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
4.225	1.0	20473	3.3004
2.9935	2.0	40946	2.7915
2.5083	3.0	61419	2.6718

Framework versions

Transformers 4.34.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.1

hugsom/ecopromptgenerator

EcoPrompt Generation

Model description

Training hyperparameters

Training results

Framework versions

hugsom/
ecopromptgenerator