merve/chatgpt-prompts-bart-long

ChatGPT Prompt Generator

This model is a fine-tuned version of BART-large on a ChatGPT prompts dataset. It achieves the following results on the evaluation set:

• Train Loss: 2.8329
• Validation Loss: 2.5015
• Epoch: 4

Intended uses & limitations

You can use this to generate ChatGPT personas. Simply input a persona like below:

from transformers import BartForConditionalGeneration, BartTokenizer

example_english_phrase = "photographer"
batch = tokenizer(example_english_phrase, return_tensors="pt")
generated_ids = model.generate(batch["input_ids"], max_new_tokens=150)
output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)

Training procedure

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
8.4973	6.3592	0
5.3145	3.2640	1
3.5899	2.8350	2
3.1044	2.6154	3
2.8329	2.5015	4

Framework versions

• Transformers 4.26.0
• TensorFlow 2.9.2
• Datasets 2.8.0
• Tokenizers 0.13.2