# hfl-rbt6-ChnSentiCorp-sentiment-classifier

This model is a fine-tuned version of [hfl/rbt6](https://huggingface.co/hfl/rbt6) on the [seamew/ChnSentiCorp](https://huggingface.co/datasets/seamew/ChnSentiCorp) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.294600	
- Accuracy: 0.933884

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- weight_decay=1e-2
- num_epochs: 3

### Training results

| Epoch | Training Loss | Validation Loss | Accuracy |    F1    | Precision |  Recall  |
|:-----:|:-------------:|:---------------:|:--------:|:--------:|:---------:|:--------:|
|   1   |   0.359700    |    0.306089     | 0.924242 | 0.926230	| 0.918699  | 0.933884 |
|   2   |   0.200600    |    0.295512	  | 0.942761 | 0.943615	| 0.946755  | 0.940496 |
|   3   |   0.105600    |    0.294600     | 0.933884 | 0.942452	| 0.951178  | 0.933884 |


### Framework versions

- Pytorch 2.0.0
- Python  3.9.12
{"language": ["zh"], "datasets": ["seamew/ChnSentiCorp"], "metrics": ["accuracy", "precision", "f1", "recall"], "pipeline_tag": "text-classification"}
transformers pytorch bert text-classification zh dataset:seamew/ChnSentiCorp autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #zh #dataset-seamew/ChnSentiCorp #autotrain_compatible #endpoints_compatible #region-us 

hfl-rbt6-ChnSentiCorp-sentiment-classifier
==========================================


This model is a fine-tuned version of hfl/rbt6 on the seamew/ChnSentiCorp dataset.
It achieves the following results on the evaluation set:


* Loss: 0.294600
* Accuracy: 0.933884


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* weight\_decay=1e-2
* num\_epochs: 3


### Training results



### Framework versions


* Pytorch 2.0.0
* Python 3.9.12



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* weight\_decay=1e-2
* num\_epochs: 3 ### Training results ### Framework versions


* Pytorch 2.0.0
* Python 3.9.12
TAGS
#transformers #pytorch #bert #text-classification #zh #dataset-seamew/ChnSentiCorp #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* weight\_decay=1e-2
* num\_epochs: 3 ### Training results ### Framework versions


* Pytorch 2.0.0
* Python 3.9.12
TAGS
#transformers #pytorch #bert #text-classification #zh #dataset-seamew/ChnSentiCorp #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* weight\_decay=1e-2
* num\_epochs: 3### Training results### Framework versions


* Pytorch 2.0.0
* Python 3.9.12