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

Loss: 0.0362

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: 4
gradient_accumulation_steps: 4
total_train_batch_size: 32
total_eval_batch_size: 4
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: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.0621	0.4779	100	0.0428
0.0465	0.9558	200	0.0362

Framework versions

Transformers 4.55.0
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1

nreHieW/qwen3-4b-instruct-2507-1epochs-non-ood

qwen3-4b-instruct-2507-1epochs-non-ood

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

nreHieW/
qwen3-4b-instruct-2507-1epochs-non-ood