--- library_name: transformers license: apache-2.0 base_model: bert-base-chinese tags: - generated_from_trainer model-index: - name: classification_1 results: [] --- # classification_1 This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0099 ## 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: 2e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | No log | 1.0 | 3 | 0.5742 | | No log | 2.0 | 6 | 0.3245 | | No log | 3.0 | 9 | 0.1796 | | 0.4633 | 4.0 | 12 | 0.0784 | | 0.4633 | 5.0 | 15 | 0.0439 | | 0.4633 | 6.0 | 18 | 0.0265 | | 0.0749 | 7.0 | 21 | 0.0163 | | 0.0749 | 8.0 | 24 | 0.0121 | | 0.0749 | 9.0 | 27 | 0.0104 | | 0.0183 | 10.0 | 30 | 0.0099 | ### Framework versions - Transformers 4.57.3 - Pytorch 2.9.0+cu126 - Datasets 4.0.0 - Tokenizers 0.22.1