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Qwen3-14B-sandbagging – AI Model by Sarim-Hash | AlphaNeural AI
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Sarim-Hash
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Qwen3-14B-sandbagging
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transformers
safetensors
qwen3
text-generation
llama-factory
full
generated_from_trainer
conversational
Qwen/Qwen3-14B
finetune
other
text-generation-inference
endpoints_compatible
us
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This model is a fine-tuned version of
/home/lukas/users/shashmi/Qwen3-14B
on the df_final 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: 1
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 2
total_train_batch_size: 8
total_eval_batch_size: 32
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: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 8.0
Training results
Framework versions
Transformers 4.57.6
Pytorch 2.7.0+cu126
Datasets 3.6.0
Tokenizers 0.22.2
