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README.md
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datasets:
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- openwebtext
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- name: llama-2-7b-hf-distill-aaronson-k4-lr1e-5-decayto0
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# llama-2-7b-hf-distill-aaronson-k4-lr1e-5-decayto0
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This model is a fine-tuned version of [/scr-ssd/cygu/weights/Llama-2-7b-hf/](https://huggingface.co//scr-ssd/cygu/weights/Llama-2-7b-hf/) on the openwebtext dataset.
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## Model description
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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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- lr_scheduler_warmup_steps: 500
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- training_steps: 5000
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### Training results
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### Framework versions
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- Transformers 4.29.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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- generated_from_trainer
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datasets:
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- openwebtext
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license: llama2
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## Model description
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Logits-based watermark distilled Llama 2 7B using the Aar \\(k=4\\) watermarking strategy in the paper [On the Learnability of Watermarks for Language Models](https://arxiv.org/abs/2312.04469).
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### Training hyperparameters
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- lr_scheduler_warmup_steps: 500
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- training_steps: 5000
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### Framework versions
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- Transformers 4.29.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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