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# bert-base-finetuned-sts-v3

This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the klue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3716
- Pearsonr: 0.9172

## 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: 4
- eval_batch_size: 4
- 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 | Pearsonr |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2265        | 1.0   | 2917  | 0.4886          | 0.8933   |
| 0.1504        | 2.0   | 5834  | 0.4374          | 0.8948   |
| 0.0982        | 3.0   | 8751  | 0.5246          | 0.8957   |
| 0.0832        | 4.0   | 11668 | 0.4387          | 0.9006   |
| 0.0751        | 5.0   | 14585 | 0.4036          | 0.9049   |
| 0.0564        | 6.0   | 17502 | 0.3828          | 0.9133   |
| 0.0488        | 7.0   | 20419 | 0.3716          | 0.9172   |
| 0.0384        | 8.0   | 23336 | 0.4060          | 0.9093   |
| 0.0365        | 9.0   | 26253 | 0.3939          | 0.9065   |
| 0.0319        | 10.0  | 29170 | 0.3953          | 0.9106   |
| 0.0262        | 11.0  | 32087 | 0.3885          | 0.9109   |
| 0.0219        | 12.0  | 35004 | 0.3724          | 0.9154   |
| 0.0188        | 13.0  | 37921 | 0.3827          | 0.9111   |
| 0.0175        | 14.0  | 40838 | 0.4103          | 0.9099   |
| 0.0144        | 15.0  | 43755 | 0.3768          | 0.9152   |
| 0.0132        | 16.0  | 46672 | 0.3868          | 0.9151   |
| 0.0125        | 17.0  | 49589 | 0.3981          | 0.9103   |
| 0.0106        | 18.0  | 52506 | 0.3808          | 0.9138   |
| 0.0095        | 19.0  | 55423 | 0.3904          | 0.9128   |
| 0.0089        | 20.0  | 58340 | 0.3885          | 0.9137   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0
- Datasets 2.7.1
- Tokenizers 0.13.2

{"license": "cc-by-sa-4.0", "tags": ["generated_from_trainer"], "datasets": ["klue"], "metrics": ["pearsonr"], "model-index": [{"name": "bert-base-finetuned-sts-v3", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "klue", "type": "klue", "config": "sts", "split": "train", "args": "sts"}, "metrics": [{"type": "pearsonr", "value": 0.9172194083849969, "name": "Pearsonr"}]}]}]}
transformers pytorch bert text-classification generated_from_trainer dataset:klue license:cc-by-sa-4.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-klue #license-cc-by-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bert-base-finetuned-sts-v3
==========================


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


* Loss: 0.3716
* Pearsonr: 0.9172


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: 4
* eval\_batch\_size: 4
* 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 4.25.1
* Pytorch 1.13.0
* Datasets 2.7.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* 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 4.25.1
* Pytorch 1.13.0
* Datasets 2.7.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-klue #license-cc-by-sa-4.0 #model-index #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
* 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 4.25.1
* Pytorch 1.13.0
* Datasets 2.7.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-klue #license-cc-by-sa-4.0 #model-index #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
* 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 4.25.1
* Pytorch 1.13.0
* Datasets 2.7.1
* Tokenizers 0.13.2