| library_name: peft | |
| license: apache-2.0 | |
| base_model: bert-base-chinese | |
| tags: | |
| - base_model:adapter:bert-base-chinese | |
| - lora | |
| - transformers | |
| metrics: | |
| - accuracy | |
| - f1 | |
| - precision | |
| - recall | |
| model-index: | |
| - name: bert-chinese-sentiment | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # bert-chinese-sentiment | |
| This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.7466 | |
| - Accuracy: 0.5 | |
| - F1: 0.0 | |
| - Precision: 0.0 | |
| - Recall: 0.0 | |
| ## 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: 0.0002 | |
| - train_batch_size: 16 | |
| - eval_batch_size: 32 | |
| - seed: 42 | |
| - 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 | |
| - num_epochs: 3 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| ### Framework versions | |
| - PEFT 0.17.1 | |
| - Transformers 4.56.1 | |
| - Pytorch 2.8.0+cu126 | |
| - Datasets 4.0.0 | |
| - Tokenizers 0.22.0 |