--- library_name: transformers license: apache-2.0 base_model: Qwen/Qwen3-32B tags: - generated_from_trainer model-index: - name: Qwen3-32B-3d-500K-50K-0.1-reverse-padzero-plus-mul-sub-99-256D-2L-8H-1024I results: [] --- # Qwen3-32B-3d-500K-50K-0.1-reverse-padzero-plus-mul-sub-99-256D-2L-8H-1024I This model is a fine-tuned version of [Qwen/Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.1047 ## 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: 0.001 - train_batch_size: 128 - eval_batch_size: 128 - seed: 42 - 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: 0.05 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:-----:|:---------------:| | No log | 0 | 0 | 3.0688 | | 1.5562 | 0.1280 | 500 | 1.5151 | | 1.386 | 0.2560 | 1000 | 1.4130 | | 1.325 | 0.3839 | 1500 | 1.2898 | | 1.2018 | 0.5119 | 2000 | 1.1987 | | 1.1801 | 0.6399 | 2500 | 1.1789 | | 1.1662 | 0.7679 | 3000 | 1.1659 | | 1.1573 | 0.8958 | 3500 | 1.1620 | | 1.1536 | 1.0238 | 4000 | 1.1548 | | 1.1511 | 1.1518 | 4500 | 1.1481 | | 1.1532 | 1.2798 | 5000 | 1.1456 | | 1.1434 | 1.4077 | 5500 | 1.1443 | | 1.1458 | 1.5357 | 6000 | 1.1405 | | 1.1395 | 1.6637 | 6500 | 1.1365 | | 1.1359 | 1.7917 | 7000 | 1.1336 | | 1.1326 | 1.9196 | 7500 | 1.1320 | | 1.1289 | 2.0476 | 8000 | 1.1304 | | 1.1277 | 2.1756 | 8500 | 1.1265 | | 1.1263 | 2.3036 | 9000 | 1.1244 | | 1.1223 | 2.4315 | 9500 | 1.1227 | | 1.1193 | 2.5595 | 10000 | 1.1197 | | 1.1178 | 2.6875 | 10500 | 1.1157 | | 1.116 | 2.8155 | 11000 | 1.1137 | | 1.1136 | 2.9434 | 11500 | 1.1136 | | 1.1108 | 3.0714 | 12000 | 1.1101 | | 1.1072 | 3.1994 | 12500 | 1.1084 | | 1.1068 | 3.3274 | 13000 | 1.1075 | | 1.106 | 3.4553 | 13500 | 1.1067 | | 1.1049 | 3.5833 | 14000 | 1.1060 | | 1.1053 | 3.7113 | 14500 | 1.1054 | | 1.104 | 3.8393 | 15000 | 1.1051 | | 1.1048 | 3.9672 | 15500 | 1.1049 | | 1.1042 | 4.0952 | 16000 | 1.1048 | | 1.1045 | 4.2232 | 16500 | 1.1047 | | 1.1049 | 4.3512 | 17000 | 1.1047 | | 1.1046 | 4.4791 | 17500 | 1.1047 | | 1.104 | 4.6071 | 18000 | 1.1047 | | 1.104 | 4.7351 | 18500 | 1.1047 | | 1.1049 | 4.8631 | 19000 | 1.1046 | | 1.1042 | 4.9910 | 19500 | 1.1047 | ### Framework versions - Transformers 4.57.1 - Pytorch 2.9.0+cu128 - Datasets 4.5.0 - Tokenizers 0.22.1