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# kc-bert_finetuned_unsmile

This model is a fine-tuned version of [beomi/kcbert-base](https://huggingface.co/beomi/kcbert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1326
- Lrap: 0.8753

## 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: 64
- eval_batch_size: 64
- 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 | Lrap   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 235  | 0.1458          | 0.8612 |
| No log        | 2.0   | 470  | 0.1280          | 0.8738 |
| 0.1685        | 3.0   | 705  | 0.1257          | 0.8791 |
| 0.1685        | 4.0   | 940  | 0.1281          | 0.8777 |
| 0.0774        | 5.0   | 1175 | 0.1326          | 0.8753 |


### Framework versions

- Transformers 4.19.4
- Pytorch 1.11.0+cu113
- Datasets 1.17.0
- Tokenizers 0.12.1

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

kc-bert\_finetuned\_unsmile
===========================


This model is a fine-tuned version of beomi/kcbert-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1326
* Lrap: 0.8753


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: 64
* eval\_batch\_size: 64
* 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 4.19.4
* Pytorch 1.11.0+cu113
* Datasets 1.17.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* 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 4.19.4
* Pytorch 1.11.0+cu113
* Datasets 1.17.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #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: 64
* eval\_batch\_size: 64
* 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 4.19.4
* Pytorch 1.11.0+cu113
* Datasets 1.17.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #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: 64
* eval\_batch\_size: 64
* 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 4.19.4
* Pytorch 1.11.0+cu113
* Datasets 1.17.0
* Tokenizers 0.12.1