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# madatnlp/kor-math-roberta-finetune

This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.3205
- Validation Loss: 1.1407
- Epoch: 26

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_bfloat16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 3.4242     | 2.0873          | 0     |
| 1.9159     | 1.6264          | 1     |
| 1.5933     | 1.4521          | 2     |
| 1.3806     | 1.3584          | 3     |
| 1.2487     | 1.2904          | 4     |
| 1.1464     | 1.2388          | 5     |
| 1.0552     | 1.2076          | 6     |
| 0.9889     | 1.1818          | 7     |
| 0.9118     | 1.1607          | 8     |
| 0.8459     | 1.1349          | 9     |
| 0.7838     | 1.1193          | 10    |
| 0.7389     | 1.1193          | 11    |
| 0.6864     | 1.1080          | 12    |
| 0.6495     | 1.1001          | 13    |
| 0.6103     | 1.1001          | 14    |
| 0.5795     | 1.0990          | 15    |
| 0.5436     | 1.0954          | 16    |
| 0.5136     | 1.0997          | 17    |
| 0.4906     | 1.0954          | 18    |
| 0.4565     | 1.1021          | 19    |
| 0.4347     | 1.1075          | 20    |
| 0.4131     | 1.1075          | 21    |
| 0.3924     | 1.1220          | 22    |
| 0.3741     | 1.1298          | 23    |
| 0.3549     | 1.1352          | 24    |
| 0.3395     | 1.1286          | 25    |
| 0.3205     | 1.1407          | 26    |


### Framework versions

- Transformers 4.18.0
- TensorFlow 2.8.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["generated_from_keras_callback"], "model-index": [{"name": "madatnlp/kor-math-roberta-finetune", "results": []}]}
transformers tf roberta fill-mask generated_from_keras_callback autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #roberta #fill-mask #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 

madatnlp/kor-math-roberta-finetune
==================================


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


* Train Loss: 0.3205
* Validation Loss: 1.1407
* Epoch: 26


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:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 1e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: mixed\_bfloat16


### Training results



### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 1e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: mixed\_bfloat16 ### Training results ### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #tf #roberta #fill-mask #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 1e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: mixed\_bfloat16 ### Training results ### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #tf #roberta #fill-mask #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 1e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: mixed\_bfloat16### Training results### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1