---
library_name: transformers
base_model: bert-base-chinese
tags:
- generated_from_trainer
model-index:
- name: bert-base-chinese-finetuned-question-answering-8
  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-base-chinese-finetuned-question-answering-8

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: 1.0682

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.6873        | 0.1842 | 500  | 1.1089          |
| 1.1046        | 0.3683 | 1000 | 0.9349          |
| 0.9793        | 0.5525 | 1500 | 0.9402          |
| 0.9477        | 0.7366 | 2000 | 0.8424          |
| 0.8951        | 0.9208 | 2500 | 0.8333          |
| 0.6411        | 1.1050 | 3000 | 0.9014          |
| 0.4946        | 1.2891 | 3500 | 0.9121          |
| 0.4887        | 1.4733 | 4000 | 0.8586          |
| 0.4875        | 1.6575 | 4500 | 0.9060          |
| 0.4483        | 1.8416 | 5000 | 0.7990          |
| 0.4079        | 2.0258 | 5500 | 0.9980          |
| 0.2337        | 2.2099 | 6000 | 1.0852          |
| 0.2342        | 2.3941 | 6500 | 1.0850          |
| 0.2239        | 2.5783 | 7000 | 1.0937          |
| 0.1853        | 2.7624 | 7500 | 1.1032          |
| 0.2009        | 2.9466 | 8000 | 1.0682          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1