chatgpt-gpt4-prompts-bart-large-cnn-samsum

This model generates ChatGPT/BingChat & GPT-3 prompts and is a fine-tuned version of philschmid/bart-large-cnn-samsum on an this dataset. It achieves the following results on the evaluation set:

• Train Loss: 1.2214
• Validation Loss: 2.7584
• Epoch: 4

Streamlit

This model supports a Streamlit Web UI to run the chatgpt-gpt4-prompts-bart-large-cnn-samsum model:

Training hyperparameters

The following hyperparameters were used during training:

• optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: float32

Training results

Train Loss	Validation Loss	Epoch
3.1982	2.6801	0
2.3601	2.5493	1
1.9225	2.5377	2
1.5465	2.6794	3
1.2214	2.7584	4

Framework versions

• Transformers 4.27.3
• TensorFlow 2.11.0
• Datasets 2.10.1
• Tokenizers 0.13.2