This model is a fine-tuned version of Qwen/Qwen3-4B on the /data/better_refiner/codeql/qwen3_nothink/full dataset. It achieves the following results on the evaluation set:

Loss: 0.3477

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: 2e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
total_train_batch_size: 32
total_eval_batch_size: 8
optimizer: Use 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: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.335	1.0	524	0.3371
0.2533	2.0	1048	0.3244
0.1747	3.0	1572	0.3477

Framework versions

Transformers 4.53.0
Pytorch 2.7.1+cu126
Datasets 3.6.0
Tokenizers 0.21.2

atac-cmu/qwen3-4b-refiner-codeql-self-nothink-full

qwen3-4b-refiner-codeql-self-nothink-full

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

atac-cmu/
qwen3-4b-refiner-codeql-self-nothink-full