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Update README.md
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README.md
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@@ -22,12 +22,30 @@ Intended for use on a student group project for Portland State University's Wint
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## Training and evaluation data
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## Training procedure
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Trained on a single RTX 3090 card.
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### Training hyperparameters
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The following hyperparameters were used during training:
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- mixed_precision_training: Native AMP
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### Training results
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{'loss': 0.0472, 'learning_rate': 1.4893617021276598e-06, 'epoch': 4.95}
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{'train_runtime': 563.2707,
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'train_samples_per_second': 1.687,
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'train_steps_per_second': 0.417,
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## Training and evaluation data
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Instruction Tuned on the creative writing dataset here: https://huggingface.co/datasets/adambjorn/UnrelatedForgettingOverhead/viewer/creative
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## Training procedure
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Trained on a single RTX 3090 card.
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Given a set of prompts:
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```python
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prompts = [
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"Write a creative short story based on the following title:",
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"Here is a title for a story. Craft a short narrative around it:",
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"Using the title given, develop a short story:",
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"Imagine a short story that starts with this title:",
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"Create a brief story with the following title:"
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]
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```
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Concatenate the prompt, the title and the story like so:
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```python
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concatenated_texts = [random.choice(prompts) + " " + title + "</s>" + "Story: " + selftext for title, selftext in zip(titles, selftexts)]
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```
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### Training hyperparameters
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The following hyperparameters were used during training:
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- mixed_precision_training: Native AMP
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### Training results
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Final results:
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{'loss': 0.0472, 'learning_rate': 1.4893617021276598e-06, 'epoch': 4.95}
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Average results:
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{'train_runtime': 563.2707,
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'train_samples_per_second': 1.687,
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'train_steps_per_second': 0.417,
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