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

Loss: 0.0420

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: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.0739	0.4292	100	0.0490
0.0444	0.8584	200	0.0421
0.021	1.2876	300	0.0407
0.027	1.7167	400	0.0392
0.015	2.1459	500	0.0418
0.0117	2.5751	600	0.0422

Framework versions

Transformers 4.55.0
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1

nreHieW/qwen3-4b-instruct-2507-3epochs-both

qwen3-4b-instruct-2507-3epochs-both

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

nreHieW/
qwen3-4b-instruct-2507-3epochs-both