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: Open In HF Spaces

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
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Dataset used to train Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum

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