--- 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-1L-8H-512I results: [] --- # Qwen3-32B-3d-500K-50K-0.1-reverse-padzero-plus-mul-sub-99-128D-1L-8H-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: 1.2386 ## 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 | 3.0552 | | 1.7001 | 0.1280 | 500 | 1.6572 | | 1.4437 | 0.2560 | 1000 | 1.4382 | | 1.4105 | 0.3839 | 1500 | 1.4093 | | 1.3962 | 0.5119 | 2000 | 1.3939 | | 1.3868 | 0.6399 | 2500 | 1.3864 | | 1.3825 | 0.7679 | 3000 | 1.3802 | | 1.3764 | 0.8958 | 3500 | 1.3763 | | 1.3749 | 1.0238 | 4000 | 1.3721 | | 1.3592 | 1.1518 | 4500 | 1.3602 | | 1.3569 | 1.2798 | 5000 | 1.3570 | | 1.3549 | 1.4077 | 5500 | 1.3529 | | 1.3519 | 1.5357 | 6000 | 1.3513 | | 1.3514 | 1.6637 | 6500 | 1.3506 | | 1.3491 | 1.7917 | 7000 | 1.3495 | | 1.3474 | 1.9196 | 7500 | 1.3481 | | 1.3461 | 2.0476 | 8000 | 1.3465 | | 1.3451 | 2.1756 | 8500 | 1.3458 | | 1.3462 | 2.3036 | 9000 | 1.3457 | | 1.3453 | 2.4315 | 9500 | 1.3452 | | 1.3434 | 2.5595 | 10000 | 1.3445 | | 1.2682 | 2.6875 | 10500 | 1.2654 | | 1.2562 | 2.8155 | 11000 | 1.2524 | | 1.2496 | 2.9434 | 11500 | 1.2480 | | 1.246 | 3.0714 | 12000 | 1.2458 | | 1.2422 | 3.1994 | 12500 | 1.2441 | | 1.24 | 3.3274 | 13000 | 1.2424 | | 1.2401 | 3.4553 | 13500 | 1.2413 | | 1.2413 | 3.5833 | 14000 | 1.2406 | | 1.2389 | 3.7113 | 14500 | 1.2398 | | 1.2375 | 3.8393 | 15000 | 1.2394 | | 1.2404 | 3.9672 | 15500 | 1.2391 | | 1.2391 | 4.0952 | 16000 | 1.2389 | | 1.2412 | 4.2232 | 16500 | 1.2387 | | 1.2408 | 4.3512 | 17000 | 1.2387 | | 1.2401 | 4.4791 | 17500 | 1.2386 | | 1.2367 | 4.6071 | 18000 | 1.2386 | | 1.2372 | 4.7351 | 18500 | 1.2386 | | 1.2393 | 4.8631 | 19000 | 1.2386 | | 1.2394 | 4.9910 | 19500 | 1.2386 | ### Framework versions - Transformers 4.57.1 - Pytorch 2.9.0+cu128 - Datasets 4.5.0 - Tokenizers 0.22.1