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# chinese-roberta-wwm-ext-finetuned2

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: 0.1448
- 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: 8
- eval_batch_size: 8
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.4081        | 1.0   | 3    | 0.9711          | 0.7273   | 0.6573 |
| 0.9516        | 2.0   | 6    | 0.8174          | 0.8182   | 0.8160 |
| 0.8945        | 3.0   | 9    | 0.6617          | 0.9091   | 0.9124 |
| 0.7042        | 4.0   | 12   | 0.5308          | 1.0      | 1.0    |
| 0.6641        | 5.0   | 15   | 0.4649          | 1.0      | 1.0    |
| 0.5731        | 6.0   | 18   | 0.4046          | 1.0      | 1.0    |
| 0.5132        | 7.0   | 21   | 0.3527          | 1.0      | 1.0    |
| 0.3999        | 8.0   | 24   | 0.3070          | 1.0      | 1.0    |
| 0.4198        | 9.0   | 27   | 0.2673          | 1.0      | 1.0    |
| 0.3677        | 10.0  | 30   | 0.2378          | 1.0      | 1.0    |
| 0.3545        | 11.0  | 33   | 0.2168          | 1.0      | 1.0    |
| 0.3237        | 12.0  | 36   | 0.1980          | 1.0      | 1.0    |
| 0.3122        | 13.0  | 39   | 0.1860          | 1.0      | 1.0    |
| 0.2802        | 14.0  | 42   | 0.1759          | 1.0      | 1.0    |
| 0.2552        | 15.0  | 45   | 0.1671          | 1.0      | 1.0    |
| 0.2475        | 16.0  | 48   | 0.1598          | 1.0      | 1.0    |
| 0.2259        | 17.0  | 51   | 0.1541          | 1.0      | 1.0    |
| 0.201         | 18.0  | 54   | 0.1492          | 1.0      | 1.0    |
| 0.2083        | 19.0  | 57   | 0.1461          | 1.0      | 1.0    |
| 0.2281        | 20.0  | 60   | 0.1448          | 1.0      | 1.0    |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.12.0+cu102
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "chinese-roberta-wwm-ext-finetuned2", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

chinese-roberta-wwm-ext-finetuned2
==================================


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: 0.1448
* 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: 8
* eval\_batch\_size: 8
* 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 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* 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 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #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: 8
* eval\_batch\_size: 8
* 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 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #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: 8
* eval\_batch\_size: 8
* 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 2.1.0
* Tokenizers 0.12.1