Grogros/cygu-llama-2-7b-sampling-watermark-distill-kth-shift256-ft-learnability_adv-lora

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cygu-llama-2-7b-sampling-watermark-distill-kth-shift256-ft-learnability_adv-lora

This model is a fine-tuned version of cygu/llama-2-7b-sampling-watermark-distill-kth-shift256 on the openwebtext dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 1e-05
• —trainbatchsize: 4
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 16
• —totaltrainbatch_size: 64
• —optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.1
• —training_steps: 2500

Training results

Framework versions

• —PEFT 0.14.0
• —Transformers 4.46.3
• —Pytorch 2.5.1.post303
• —Datasets 3.2.0
• —Tokenizers 0.20.3