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# chinese-roberta-wwm-ext-finetuned

This model is a fine-tuned version of [hfl/chinese-roberta-wwm-ext](https://huggingface.co/hfl/chinese-roberta-wwm-ext) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2139
- Accuracy: 1.0
- F1: 1.0

## 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0107        | 1.0   | 1    | 0.8782          | 0.6      | 0.4500 |
| 0.8418        | 2.0   | 2    | 0.7816          | 0.6      | 0.4500 |
| 0.7572        | 3.0   | 3    | 0.7080          | 0.6      | 0.4500 |
| 0.6794        | 4.0   | 4    | 0.6487          | 0.8      | 0.7810 |
| 0.7444        | 5.0   | 5    | 0.5972          | 0.8      | 0.7810 |
| 0.68          | 6.0   | 6    | 0.5516          | 0.9      | 0.8967 |
| 0.5622        | 7.0   | 7    | 0.5103          | 0.9      | 0.8967 |
| 0.5131        | 8.0   | 8    | 0.4692          | 0.9      | 0.8967 |
| 0.5941        | 9.0   | 9    | 0.4285          | 1.0      | 1.0    |
| 0.5093        | 10.0  | 10   | 0.3899          | 1.0      | 1.0    |
| 0.4149        | 11.0  | 11   | 0.3549          | 1.0      | 1.0    |
| 0.4634        | 12.0  | 12   | 0.3248          | 1.0      | 1.0    |
| 0.3982        | 13.0  | 13   | 0.2985          | 1.0      | 1.0    |
| 0.352         | 14.0  | 14   | 0.2756          | 1.0      | 1.0    |
| 0.3633        | 15.0  | 15   | 0.2570          | 1.0      | 1.0    |
| 0.3729        | 16.0  | 16   | 0.2420          | 1.0      | 1.0    |
| 0.2934        | 17.0  | 17   | 0.2303          | 1.0      | 1.0    |
| 0.308         | 18.0  | 18   | 0.2220          | 1.0      | 1.0    |
| 0.2977        | 19.0  | 19   | 0.2166          | 1.0      | 1.0    |
| 0.2969        | 20.0  | 20   | 0.2139          | 1.0      | 1.0    |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.12.0+cu102
- Datasets 1.18.4
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "chinese-roberta-wwm-ext-finetuned", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

chinese-roberta-wwm-ext-finetuned
=================================


This model is a fine-tuned version of hfl/chinese-roberta-wwm-ext on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2139
* Accuracy: 1.0
* F1: 1.0


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: 10
* eval\_batch\_size: 10
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.12.0+cu102
* Datasets 1.18.4
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 10
* eval\_batch\_size: 10
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.12.0+cu102
* Datasets 1.18.4
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 10
* eval\_batch\_size: 10
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.12.0+cu102
* Datasets 1.18.4
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 10
* eval\_batch\_size: 10
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.12.0+cu102
* Datasets 1.18.4
* Tokenizers 0.12.1