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# indobert-distilled-optimized-for-classification

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the indonlu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5991
- Accuracy: 0.9024
- F1: 0.9021

## 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: 5.262995179171344e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 33
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.2938        | 1.0   | 688  | 0.8433          | 0.8484   | 0.8513 |
| 0.711         | 2.0   | 1376 | 0.6408          | 0.8881   | 0.8878 |
| 0.4416        | 3.0   | 2064 | 0.7964          | 0.8794   | 0.8793 |
| 0.2907        | 4.0   | 2752 | 0.7559          | 0.8897   | 0.8900 |
| 0.2065        | 5.0   | 3440 | 0.6892          | 0.8968   | 0.8974 |
| 0.1574        | 6.0   | 4128 | 0.6881          | 0.8913   | 0.8906 |
| 0.1131        | 7.0   | 4816 | 0.6224          | 0.8984   | 0.8982 |
| 0.0865        | 8.0   | 5504 | 0.6312          | 0.8976   | 0.8970 |
| 0.0678        | 9.0   | 6192 | 0.6187          | 0.8992   | 0.8989 |
| 0.0526        | 10.0  | 6880 | 0.5991          | 0.9024   | 0.9021 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["indonlu"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "indobert-distilled-optimized-for-classification", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "indonlu", "type": "indonlu", "args": "smsa"}, "metrics": [{"type": "accuracy", "value": 0.9023809523809524, "name": "Accuracy"}, {"type": "f1", "value": 0.9020516403647337, "name": "F1"}]}]}]}
transformers pytorch distilbert text-classification generated_from_trainer dataset:indonlu license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-indonlu #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

indobert-distilled-optimized-for-classification
===============================================


This model is a fine-tuned version of distilbert-base-uncased on the indonlu dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5991
* Accuracy: 0.9024
* F1: 0.9021


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: 5.262995179171344e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 33
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.262995179171344e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 33
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-indonlu #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.262995179171344e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 33
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-indonlu #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.262995179171344e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 33
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.1.0
* Tokenizers 0.12.1