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# 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

{"license": "gpl-3.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "albert-base-chinese-finetuned-qqp", "results": []}]}
transformers pytorch albert text-classification generated_from_trainer license:gpl-3.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #albert #text-classification #generated_from_trainer #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #region-us 

albert-base-chinese-finetuned-qqp
=================================


This model is a fine-tuned version of 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



### Framework versions


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



### 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.9.0
* Tokenizers 0.13.0.dev0
TAGS
#transformers #pytorch #albert #text-classification #generated_from_trainer #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.9.0
* Tokenizers 0.13.0.dev0
TAGS
#transformers #pytorch #albert #text-classification #generated_from_trainer #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


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