4373913827
Model: cygu/llama-2-7b-logit-watermark-distill-kgw-k1-gamma0.25-delta2 Source: Original Platform
34 lines
837 B
Markdown
34 lines
837 B
Markdown
---
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tags:
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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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---
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## Model description
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Logit-based watermark distilled Llama 2 7B using the KGW \\(k=1, \gamma=0.25, \delta=2\\) 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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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 4
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- total_train_batch_size: 64
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- total_eval_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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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 |