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# bert-base-finetuned-sts

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: 0.4115
- Pearsonr: 0.8756
- F1: 0.8417

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pearsonr | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.7836        | 1.0   | 365  | 0.5507          | 0.8435   | 0.8121 |
| 0.1564        | 2.0   | 730  | 0.4396          | 0.8495   | 0.8136 |
| 0.0989        | 3.0   | 1095 | 0.4115          | 0.8756   | 0.8417 |
| 0.0682        | 4.0   | 1460 | 0.4466          | 0.8746   | 0.8449 |


### Framework versions

- Transformers 4.10.2
- Pytorch 1.7.1
- Datasets 1.12.1
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "datasets": ["klue"], "metrics": ["pearsonr", "f1"], "model-index": [{"name": "bert-base-finetuned-sts", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "klue", "type": "klue", "args": "sts"}, "metrics": [{"type": "pearsonr", "value": 0.8756147003619346, "name": "Pearsonr"}, {"type": "f1", "value": 0.8416666666666667, "name": "F1"}]}]}]}
transformers pytorch bert text-classification generated_from_trainer dataset:klue model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-klue #model-index #autotrain_compatible #endpoints_compatible #region-us 

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


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: 0.4115
* Pearsonr: 0.8756
* F1: 0.8417


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: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 4


### Training results



### Framework versions


* Transformers 4.10.2
* Pytorch 1.7.1
* Datasets 1.12.1
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.10.2
* Pytorch 1.7.1
* Datasets 1.12.1
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-klue #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.10.2
* Pytorch 1.7.1
* Datasets 1.12.1
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-klue #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 4### Training results### Framework versions


* Transformers 4.10.2
* Pytorch 1.7.1
* Datasets 1.12.1
* Tokenizers 0.10.3