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# grow_classification_kobert-lm

This model is a fine-tuned version of [monologg/kobert-lm](https://huggingface.co/monologg/kobert-lm) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0751
- Accuracy: 0.6946
- F1: 0.6970

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8394        | 1.0   | 329  | 0.8209          | 0.6664   | 0.6719 |
| 0.5789        | 2.0   | 658  | 0.8653          | 0.6962   | 0.7018 |
| 0.5125        | 3.0   | 987  | 0.9554          | 0.6942   | 0.6919 |
| 0.4852        | 4.0   | 1316 | 0.9838          | 0.7057   | 0.7120 |
| 0.464         | 5.0   | 1645 | 0.9969          | 0.6910   | 0.6934 |
| 0.4519        | 6.0   | 1974 | 1.0354          | 0.6918   | 0.6973 |
| 0.4437        | 7.0   | 2303 | 1.0301          | 0.6871   | 0.6940 |
| 0.4342        | 8.0   | 2632 | 1.0676          | 0.6950   | 0.6972 |
| 0.4299        | 9.0   | 2961 | 1.0691          | 0.6962   | 0.6984 |
| 0.4276        | 10.0  | 3290 | 1.0751          | 0.6946   | 0.6970 |


### 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-lm", "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-lm
===============================


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


* Loss: 1.0751
* Accuracy: 0.6946
* F1: 0.6970


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