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cygu-llama-2-7b-sampling-watermark-distill-kth-shift256-ft-learnability_adv-lora – AI Model by Grogros | AlphaNeural AI
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cygu-llama-2-7b-sampling-watermark-distill-kth-shift256-ft-learnability_adv-lora
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peft
tensorboard
safetensors
generated_from_trainer
openwebtext
cygu/llama-2-7b-sampling-watermark-distill-kth-shift256
adapter
llama2
us
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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
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_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
