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--- |
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license: bigscience-bloom-rail-1.0 |
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base_model: bigscience/bloom-1b7 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Bloom-1b7-creative-writing-IT |
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results: [] |
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--- |
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# Bloom-1b7-creative-writing-IT |
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This model is a fine-tuned version of [bigscience/bloom-1b7](https://huggingface.co./bigscience/bloom-1b7) on an a creative writing - short story dataset. |
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https://huggingface.co./datasets/adambjorn/UnrelatedForgettingOverhead/viewer/creative |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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Training and evaluation data here: https://huggingface.co./datasets/adambjorn/UnrelatedForgettingOverhead/viewer/creative |
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## Training procedure |
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The model was instruction tuned on the dataset in the following way: |
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Given the set of promts: |
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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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each training example is generated by concatenating one of the prompts with the 'title' and 'selftext' in the following way: |
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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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- learning_rate: 5e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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Final reported loss: {'loss': 0.0135, 'grad_norm': 0.6041152477264404, 'learning_rate': 7.446808510638299e-07, 'epoch': 9.89} |
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Average over tuning: {'train_runtime': 1111.4187, 'train_samples_per_second': 1.71, 'train_steps_per_second': 0.423, 'train_loss': 0.4682149670225509, 'epoch': 9.89} |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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