metadata

license: apache-2.0
tags:
  - generated_from_keras_callback
model-index:
  - name: chatgpt-prompt-generator-v12
    results: []
datasets:
  - fka/awesome-chatgpt-prompts

ChatGPT Prompt Generator v12

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

Train Loss: 2.4800
Validation Loss: 2.7320
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
5.3808	3.3133	0
3.2642	3.0104	1
2.8886	2.8600	2
2.6594	2.7949	3
2.4800	2.7320	4

Framework versions

Transformers 4.26.1
TensorFlow 2.11.0
Datasets 2.10.1
Tokenizers 0.13.2