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Grogros-gpt2-kgw-k1-delta2.0-Scratch-learnability_adv-lora – AI Model by Grogros | AlphaNeural AI

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Grogros/
Grogros-gpt2-kgw-k1-delta2.0-Scratch-learnability_adv-lora

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Grogros-gpt2-kgw-k1-delta2.0-Scratch-learnability_adv-lora

This model is a fine-tuned version of Grogros/gpt2-kgw-k1-delta2.0-Scratch 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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
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 0.20.4