EcoPrompt Generation
This model is a fine-tuned version of gpt2 on an ecoprompt dataset. It achieves the following results on the evaluation set:
- Loss: 2.6718
Model description
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
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Base model
openai-community/gpt2