---
license: gpl-3.0
base_model: ckiplab/bert-base-chinese
tags:
- generated_from_trainer
model-index:
- name: bert-base-chinese-finetuned-QA-b8
  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-QA-b8

This model is a fine-tuned version of [ckiplab/bert-base-chinese](https://huggingface.co/ckiplab/bert-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3405

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.9325        | 0.14  | 500   | 1.2076          |
| 1.1199        | 0.29  | 1000  | 1.0315          |
| 1.0118        | 0.43  | 1500  | 0.9836          |
| 0.9398        | 0.58  | 2000  | 0.9762          |
| 0.9526        | 0.72  | 2500  | 0.9374          |
| 0.9142        | 0.87  | 3000  | 0.8783          |
| 0.8265        | 1.01  | 3500  | 0.9919          |
| 0.6091        | 1.16  | 4000  | 0.9613          |
| 0.6303        | 1.3   | 4500  | 0.9769          |
| 0.6161        | 1.45  | 5000  | 0.9882          |
| 0.6109        | 1.59  | 5500  | 0.9160          |
| 0.5887        | 1.73  | 6000  | 0.9105          |
| 0.5811        | 1.88  | 6500  | 0.9812          |
| 0.5638        | 2.02  | 7000  | 1.0669          |
| 0.4174        | 2.17  | 7500  | 1.2101          |
| 0.3958        | 2.31  | 8000  | 1.2186          |
| 0.4032        | 2.46  | 8500  | 1.1691          |
| 0.4183        | 2.6   | 9000  | 1.0890          |
| 0.4247        | 2.75  | 9500  | 1.0721          |
| 0.3917        | 2.89  | 10000 | 1.1714          |
| 0.3738        | 3.04  | 10500 | 1.1794          |
| 0.29          | 3.18  | 11000 | 1.2494          |
| 0.326         | 3.32  | 11500 | 1.2822          |
| 0.3076        | 3.47  | 12000 | 1.3214          |
| 0.3071        | 3.61  | 12500 | 1.2968          |
| 0.2797        | 3.76  | 13000 | 1.3410          |
| 0.3192        | 3.9   | 13500 | 1.3405          |


### Framework versions

- Transformers 4.34.0
- Pytorch 1.13.1+cu116
- Datasets 2.14.5
- Tokenizers 0.14.1