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# Comment_Score_By_douban_-finetuned-financial_data

This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8968
- Mse: 0.8968
- Rmse: 0.9470
- Mae: 0.7104
- R2: 0.4941
- Smape: 24.0094

## 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: 128
- eval_batch_size: 20
- 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 | Mse    | Rmse   | Mae    | R2     | Smape   |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:-------:|
| No log        | 1.0   | 169  | 0.8968          | 0.8968 | 0.9470 | 0.7104 | 0.4941 | 24.0094 |
| No log        | 2.0   | 338  | 0.6792          | 0.6792 | 0.8241 | 0.6188 | 0.6169 | 21.1323 |
| 0.8399        | 3.0   | 507  | 0.6845          | 0.6845 | 0.8274 | 0.6031 | 0.6138 | 20.6587 |
| 0.8399        | 4.0   | 676  | 0.6598          | 0.6598 | 0.8123 | 0.5881 | 0.6278 | 20.1132 |
| 0.8399        | 5.0   | 845  | 0.6820          | 0.6820 | 0.8258 | 0.5909 | 0.6153 | 20.1342 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.12.1+cu113
- Datasets 2.9.0
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "model-index": [{"name": "Comment_Score_By_douban_-finetuned-financial_data", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

Comment\_Score\_By\_douban\_-finetuned-financial\_data
======================================================


This model is a fine-tuned version of bert-base-chinese on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.8968
* Mse: 0.8968
* Rmse: 0.9470
* Mae: 0.7104
* R2: 0.4941
* Smape: 24.0094


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: 128
* eval\_batch\_size: 20
* 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 4.26.0
* Pytorch 1.12.1+cu113
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 128
* eval\_batch\_size: 20
* 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 4.26.0
* Pytorch 1.12.1+cu113
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 128
* eval\_batch\_size: 20
* 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 4.26.0
* Pytorch 1.12.1+cu113
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 128
* eval\_batch\_size: 20
* 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 4.26.0
* Pytorch 1.12.1+cu113
* Datasets 2.9.0
* Tokenizers 0.13.2