chatgpt-prompts-bart-long
| Property | Value |
|---|---|
| Base Model | BART-large |
| License | Apache 2.0 |
| Training Dataset | fka/awesome-chatgpt-prompts |
| Framework | TensorFlow 2.9.2, Transformers 4.26.0 |
What is chatgpt-prompts-bart-long?
This is a specialized language model fine-tuned on the BART-large architecture for generating ChatGPT prompts and personas. The model has been trained on the awesome-chatgpt-prompts dataset and demonstrates strong performance with a final validation loss of 2.5015 after 4 epochs of training.
Implementation Details
The model utilizes the AdamWeightDecay optimizer with a learning rate of 2e-05 and implements float32 precision training. The training process showed consistent improvement across 5 epochs, with the loss decreasing from 8.4973 to 2.8329.
- Optimized with AdamWeightDecay (beta_1=0.9, beta_2=0.999)
- Weight decay rate of 0.01
- Trained using Transformers 4.26.0 and TensorFlow 2.9.2
Core Capabilities
- Generates contextually relevant ChatGPT personas
- Supports batch processing for multiple prompt generations
- Maximum token generation limit of 150 tokens
- Easy integration with the Transformers library
Frequently Asked Questions
Q: What makes this model unique?
This model specializes in generating ChatGPT prompts and personas, fine-tuned specifically for this purpose on the BART-large architecture. Its training process shows significant optimization, achieving a strong validation loss of 2.5015.
Q: What are the recommended use cases?
The model is ideal for generating creative ChatGPT personas and prompts. It can be easily implemented using the Transformers library, making it suitable for applications requiring automated prompt generation or persona creation for conversational AI systems.
