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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
