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---
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
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