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Qwen-Backdoored-Test – AI Model by linlinaty | AlphaNeural AI

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linlinaty/
Qwen-Backdoored-Test

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text-generation

Qwen/Qwen2.5-1.5B

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Qwen-Backdoored-Test

This model is a fine-tuned version of Qwen/Qwen2.5-1.5B on the None 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: 0.0001
train_batch_size: 2
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 4
total_train_batch_size: 16
total_eval_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Framework versions

PEFT 0.19.1
Transformers 5.13.0
Pytorch 2.10.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2