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--- |
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license: other |
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datasets: |
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- Open-Orca/OpenOrca |
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- ehartford/wizard_vicuna_70k_unfiltered |
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tags: |
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- code |
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- prompt |
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- reverse prompt |
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widget: |
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- text: "The results on conditioned open-ended language generation are impressive, having shown to generalize to new tasks, handle code, or take non-text data as input. Besides the improved transformer architecture and massive unsupervised training data, better decoding methods have also played an important role.\n [REVERSED-PROMPT] " |
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example_title: "reverse prompt" |
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--- |
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# core-prompt-reverser-opt-1.3b |
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This model is a fine-tuned version of [ss5](https://huggingface.co/ss5) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2950 |
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- Accuracy: 0.7084 |
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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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More information needed |
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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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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 1.0 |
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### Training results |
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### Framework versions |
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- Transformers 4.33.0.dev0 |
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- Pytorch 2.1.0.dev20230605+cu121 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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