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qwen36-27b-cyber-lora – AI Model by Asilarkness | AlphaNeural AI
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Asilarkness
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qwen36-27b-cyber-lora
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peft
safetensors
adapter
lora
transformers
text-generation
Qwen/Qwen3.6-27B
apache-2.0
us
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qwen36-27b-cyber-lora
This model is a fine-tuned version of
Qwen/Qwen3.6-27B
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.7466
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: 5e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 21
num_epochs: 2.0
Training results
Training Loss
Epoch
Step
Validation Loss
1.1136
0.2860
100
1.1353
0.9834
0.5719
200
1.0500
0.9057
0.8579
300
0.9419
0.5367
1.1430
400
0.8974
0.5223
1.4290
500
0.8172
0.4351
1.7149
600
0.7637
0.4466
2.0
700
0.7466
Framework versions
PEFT 0.20.0
Transformers 5.14.1
Pytorch 2.11.0+cu130
Datasets 5.0.1
Tokenizers 0.22.2
