---
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
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# 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