This model is a fine-tuned version of Qwen/Qwen3-4B-Instruct-2507 on the appworld_distillation_sft_v2 dataset. It achieves the following results on the evaluation set:

Loss: 0.7486

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-06
train_batch_size: 4
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
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: 30.0

Training results

Training Loss	Epoch	Step	Validation Loss
1.7313	1.0	2	1.7900
1.6378	2.0	4	1.5365
1.1356	3.0	6	1.1186
0.9041	4.0	8	0.9372
0.8762	5.0	10	0.8529
0.7807	6.0	12	0.8198
0.7323	7.0	14	0.7646
0.6814	8.0	16	0.7229
0.6211	9.0	18	0.6847
0.5738	10.0	20	0.6639
0.5171	11.0	22	0.6499
0.4868	12.0	24	0.6385
0.4371	13.0	26	0.6327
0.407	14.0	28	0.6306
0.3924	15.0	30	0.6330
0.3505	16.0	32	0.6393
0.3339	17.0	34	0.6493
0.3086	18.0	36	0.6623
0.2803	19.0	38	0.6748
0.2687	20.0	40	0.6873
0.25	21.0	42	0.6983
0.2306	22.0	44	0.7100
0.2168	23.0	46	0.7205
0.2125	24.0	48	0.7301
0.2031	25.0	50	0.7378
0.1975	26.0	52	0.7433
0.2001	27.0	54	0.7474
0.1953	28.0	56	0.7487
0.1895	29.0	58	0.7487
0.1976	30.0	60	0.7486

Framework versions

Transformers 4.52.4
Pytorch 2.8.0+cu128
Datasets 3.6.0
Tokenizers 0.21.1

huseyinatahaninan/appworld_distillation_sft_v2-SFT-Qwen3-4B-Instruct-2507

appworld_distillation_sft_v2-SFT-Qwen3-4B-Instruct-2507

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

huseyinatahaninan/
appworld_distillation_sft_v2-SFT-Qwen3-4B-Instruct-2507