--- 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-99-128D-3L-4H-512I results: [] --- # Qwen3-32B-3d-500K-50K-0.1-reverse-padzero-plus-mul-sub-99-128D-3L-4H-512I 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: 1.1212 ## 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 | 3.0614 | | 1.6535 | 0.1280 | 500 | 1.6090 | | 1.3963 | 0.2560 | 1000 | 1.3822 | | 1.2419 | 0.3839 | 1500 | 1.2429 | | 1.2233 | 0.5119 | 2000 | 1.2209 | | 1.2103 | 0.6399 | 2500 | 1.2140 | | 1.2012 | 0.7679 | 3000 | 1.1994 | | 1.1928 | 0.8958 | 3500 | 1.1917 | | 1.1876 | 1.0238 | 4000 | 1.1861 | | 1.1798 | 1.1518 | 4500 | 1.1803 | | 1.1794 | 1.2798 | 5000 | 1.1770 | | 1.1759 | 1.4077 | 5500 | 1.1750 | | 1.1731 | 1.5357 | 6000 | 1.1742 | | 1.1711 | 1.6637 | 6500 | 1.1695 | | 1.1673 | 1.7917 | 7000 | 1.1675 | | 1.1663 | 1.9196 | 7500 | 1.1637 | | 1.1599 | 2.0476 | 8000 | 1.1600 | | 1.157 | 2.1756 | 8500 | 1.1581 | | 1.1534 | 2.3036 | 9000 | 1.1528 | | 1.1492 | 2.4315 | 9500 | 1.1486 | | 1.1431 | 2.5595 | 10000 | 1.1431 | | 1.1404 | 2.6875 | 10500 | 1.1388 | | 1.139 | 2.8155 | 11000 | 1.1358 | | 1.1352 | 2.9434 | 11500 | 1.1336 | | 1.1312 | 3.0714 | 12000 | 1.1288 | | 1.13 | 3.1994 | 12500 | 1.1269 | | 1.1265 | 3.3274 | 13000 | 1.1286 | | 1.1246 | 3.4553 | 13500 | 1.1271 | | 1.1225 | 3.5833 | 14000 | 1.1235 | | 1.1224 | 3.7113 | 14500 | 1.1223 | | 1.1207 | 3.8393 | 15000 | 1.1221 | | 1.1218 | 3.9672 | 15500 | 1.1215 | | 1.1207 | 4.0952 | 16000 | 1.1215 | | 1.1216 | 4.2232 | 16500 | 1.1213 | | 1.1221 | 4.3512 | 17000 | 1.1212 | | 1.1213 | 4.4791 | 17500 | 1.1212 | | 1.1206 | 4.6071 | 18000 | 1.1212 | | 1.1204 | 4.7351 | 18500 | 1.1212 | | 1.1216 | 4.8631 | 19000 | 1.1212 | | 1.1209 | 4.9910 | 19500 | 1.1212 | ### Framework versions - Transformers 4.57.1 - Pytorch 2.9.0+cu128 - Datasets 4.5.0 - Tokenizers 0.22.1