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# madatnlp/rob-large-krmath2

This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0707
- Validation Loss: 0.2571
- Epoch: 17

## 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': 'SGD', 'learning_rate': 0.01, 'decay': 0.0, 'momentum': 0.9, 'nesterov': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 1.7479     | 1.5215          | 0     |
| 1.1286     | 0.7513          | 1     |
| 1.2498     | 0.9242          | 2     |
| 1.0213     | 0.7140          | 3     |
| 0.8002     | 0.6080          | 4     |
| 0.5895     | 0.3721          | 5     |
| 0.4699     | 0.3392          | 6     |
| 0.3064     | 0.2599          | 7     |
| 0.2803     | 0.2360          | 8     |
| 0.2162     | 0.3075          | 9     |
| 0.1878     | 0.2652          | 10    |
| 0.1635     | 0.1618          | 11    |
| 0.1342     | 0.1061          | 12    |
| 0.1058     | 0.2906          | 13    |
| 0.0869     | 0.3535          | 14    |
| 0.0704     | 0.2090          | 15    |
| 0.0608     | 0.1777          | 16    |
| 0.0707     | 0.2571          | 17    |


### Framework versions

- Transformers 4.19.2
- TensorFlow 2.8.2
- Datasets 2.2.2
- Tokenizers 0.12.1

{"tags": ["generated_from_keras_callback"], "model-index": [{"name": "madatnlp/rob-large-krmath2", "results": []}]}
transformers tf roberta text-classification generated_from_keras_callback autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #roberta #text-classification #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 

madatnlp/rob-large-krmath2
==========================


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


* Train Loss: 0.0707
* Validation Loss: 0.2571
* Epoch: 17


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': 'SGD', 'learning\_rate': 0.01, 'decay': 0.0, 'momentum': 0.9, 'nesterov': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.19.2
* TensorFlow 2.8.2
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'SGD', 'learning\_rate': 0.01, 'decay': 0.0, 'momentum': 0.9, 'nesterov': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.19.2
* TensorFlow 2.8.2
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #tf #roberta #text-classification #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'SGD', 'learning\_rate': 0.01, 'decay': 0.0, 'momentum': 0.9, 'nesterov': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.19.2
* TensorFlow 2.8.2
* Datasets 2.2.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #tf #roberta #text-classification #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'SGD', 'learning\_rate': 0.01, 'decay': 0.0, 'momentum': 0.9, 'nesterov': False}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.19.2
* TensorFlow 2.8.2
* Datasets 2.2.2
* Tokenizers 0.12.1