---
license: gpl-3.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: albert-base-chinese-finetuned-qqp
  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. -->

# albert-base-chinese-finetuned-qqp

This model is a fine-tuned version of [ckiplab/albert-base-chinese](https://huggingface.co/ckiplab/albert-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3385688364505768
- Accuracy: 0.8357142857142857
- F1: 0.8244274809160306

## 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: 2e-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |      F1  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| No log        | 1.0   |  30  | 0.654749        | 0.642857 | 0.719101 |
| No log        | 2.0   |  60  | 0.614816        | 0.728571 | 0.707692 |
| No log        | 3.0   |  90  | 0.443354        | 0.807143 | 0.802920 |
| No log        | 4.0   | 120  | 0.338569        | 0.835714 | 0.824427 |
| No log		    | 5.0   | 150  | 0.339324        | 0.828571 | 0.806452 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.0.dev0