This model is a fine-tuned version of Qwen/Qwen3-4B-Instruct-2507 on the synthetic_deepcoder_partial_edits_ood_train dataset. It achieves the following results on the evaluation set:

Loss: 0.2542

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: 2
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
total_train_batch_size: 64
total_eval_batch_size: 8
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: 0.1
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.2699	0.9926	100	0.2451
0.1766	1.9826	200	0.2407
0.1219	2.9727	300	0.2543
0.1219	3.0	303	0.2542

Framework versions

Transformers 5.6.0
Pytorch 2.11.0+cu130
Datasets 4.0.0
Tokenizers 0.23.0-rc0

nreHieW/minimal_editing_teacher_sft

qwen3-4b-instruct-2507

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

nreHieW/
minimal_editing_teacher_sft