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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_keras_callback |
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datasets: |
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- fka/awesome-chatgpt-prompts |
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base_model: BART-large |
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model-index: |
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- name: chatgpt-prompts-bart-long |
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results: [] |
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--- |
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# ChatGPT Prompt Generator |
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This model is a fine-tuned version of [BART-large](https://huggingface.co/facebook/bart-large) on a ChatGPT prompts dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 2.8329 |
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- Validation Loss: 2.5015 |
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- Epoch: 4 |
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## Intended uses & limitations |
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You can use this to generate ChatGPT personas. Simply input a persona like below: |
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``` |
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from transformers import BartForConditionalGeneration, BartTokenizer |
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example_english_phrase = "photographer" |
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batch = tokenizer(example_english_phrase, return_tensors="pt") |
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generated_ids = model.generate(batch["input_ids"], max_new_tokens=150) |
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output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True) |
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``` |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- 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} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 8.4973 | 6.3592 | 0 | |
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| 5.3145 | 3.2640 | 1 | |
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| 3.5899 | 2.8350 | 2 | |
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| 3.1044 | 2.6154 | 3 | |
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| 2.8329 | 2.5015 | 4 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- TensorFlow 2.9.2 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
