--- 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-99-512D-1L-2H-2048I results: [] --- # Qwen3-32B-3d-500K-50K-0.1-reverse-padzero-plus-mul-sub-99-512D-1L-2H-2048I 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: 1.4160 ## 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 | 3.1291 | | 1.589 | 0.1280 | 500 | 1.5825 | | 1.4924 | 0.2560 | 1000 | 1.4859 | | 1.467 | 0.3839 | 1500 | 1.4616 | | 1.4526 | 0.5119 | 2000 | 1.4497 | | 1.4459 | 0.6399 | 2500 | 1.4484 | | 1.4409 | 0.7679 | 3000 | 1.4432 | | 1.436 | 0.8958 | 3500 | 1.4381 | | 1.4363 | 1.0238 | 4000 | 1.4355 | | 1.4326 | 1.1518 | 4500 | 1.4358 | | 1.4329 | 1.2798 | 5000 | 1.4331 | | 1.4326 | 1.4077 | 5500 | 1.4303 | | 1.431 | 1.5357 | 6000 | 1.4292 | | 1.4314 | 1.6637 | 6500 | 1.4299 | | 1.4279 | 1.7917 | 7000 | 1.4279 | | 1.4255 | 1.9196 | 7500 | 1.4270 | | 1.4249 | 2.0476 | 8000 | 1.4260 | | 1.4236 | 2.1756 | 8500 | 1.4248 | | 1.4256 | 2.3036 | 9000 | 1.4251 | | 1.4245 | 2.4315 | 9500 | 1.4241 | | 1.4215 | 2.5595 | 10000 | 1.4224 | | 1.421 | 2.6875 | 10500 | 1.4220 | | 1.4233 | 2.8155 | 11000 | 1.4211 | | 1.4218 | 2.9434 | 11500 | 1.4208 | | 1.4193 | 3.0714 | 12000 | 1.4199 | | 1.4176 | 3.1994 | 12500 | 1.4191 | | 1.4163 | 3.3274 | 13000 | 1.4186 | | 1.4163 | 3.4553 | 13500 | 1.4179 | | 1.4184 | 3.5833 | 14000 | 1.4174 | | 1.4158 | 3.7113 | 14500 | 1.4169 | | 1.4149 | 3.8393 | 15000 | 1.4166 | | 1.4175 | 3.9672 | 15500 | 1.4165 | | 1.4163 | 4.0952 | 16000 | 1.4163 | | 1.4183 | 4.2232 | 16500 | 1.4161 | | 1.4176 | 4.3512 | 17000 | 1.4161 | | 1.4172 | 4.4791 | 17500 | 1.4161 | | 1.4137 | 4.6071 | 18000 | 1.4160 | | 1.4146 | 4.7351 | 18500 | 1.4160 | | 1.4162 | 4.8631 | 19000 | 1.4160 | | 1.4164 | 4.9910 | 19500 | 1.4160 | ### Framework versions - Transformers 4.57.1 - Pytorch 2.9.0+cu128 - Datasets 4.5.0 - Tokenizers 0.22.1