---
library_name: transformers
language:
- zh
license: apache-2.0
base_model: hfl/chinese-bert-wwm-ext
tags:
- generated_from_trainer
datasets:
- chinese_paragraph_relevance
metrics:
- accuracy
model-index:
- name: chinese_paragraph_bert-ext
  results:
  - task:
      name: Multiple Choice
      type: multiple-choice
    dataset:
      name: Chinese Relevance Paragraphs
      type: chinese_paragraph_relevance
      args: relevant_paragraph
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9617813229560852
---

<!-- 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. -->

# chinese_paragraph_bert-ext

This model is a fine-tuned version of [hfl/chinese-bert-wwm-ext](https://huggingface.co/hfl/chinese-bert-wwm-ext) on the Chinese Relevance Paragraphs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1717
- Accuracy: 0.9618

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1