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# grow_classification_kobert

This model is a fine-tuned version of [monologg/kobert](https://huggingface.co/monologg/kobert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0859
- Accuracy: 0.6954
- F1: 0.6969

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9241        | 1.0   | 329  | 0.8600          | 0.6565   | 0.6569 |
| 0.599         | 2.0   | 658  | 0.8925          | 0.6942   | 0.6997 |
| 0.53          | 3.0   | 987  | 0.9136          | 0.6930   | 0.6875 |
| 0.4948        | 4.0   | 1316 | 0.9813          | 0.7037   | 0.7087 |
| 0.467         | 5.0   | 1645 | 1.0175          | 0.7006   | 0.7058 |
| 0.4549        | 6.0   | 1974 | 1.0363          | 0.7025   | 0.7051 |
| 0.4457        | 7.0   | 2303 | 1.0335          | 0.7057   | 0.7107 |
| 0.4367        | 8.0   | 2632 | 1.0678          | 0.6986   | 0.6981 |
| 0.4319        | 9.0   | 2961 | 1.0868          | 0.6978   | 0.6962 |
| 0.4277        | 10.0  | 3290 | 1.0859          | 0.6954   | 0.6969 |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "grow_classification_kobert", "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 

grow\_classification\_kobert
============================


This model is a fine-tuned version of monologg/kobert on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 1.0859
* Accuracy: 0.6954
* F1: 0.6969


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: 10


### Training results



### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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: 10 ### Training results ### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
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: 10 ### Training results ### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3