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# mlm-20230503-indobert-base-p2-002

This model is a fine-tuned version of [indobenchmark/indobert-base-p2](https://huggingface.co/indobenchmark/indobert-base-p2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9160

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 284  | 4.0534          |
| 4.7356        | 2.0   | 568  | 3.3071          |
| 4.7356        | 3.0   | 852  | 2.9974          |
| 3.166         | 4.0   | 1136 | 2.7331          |
| 3.166         | 5.0   | 1420 | 2.5351          |
| 2.6688        | 6.0   | 1704 | 2.4613          |
| 2.6688        | 7.0   | 1988 | 2.3245          |
| 2.4034        | 8.0   | 2272 | 2.2535          |
| 2.2327        | 9.0   | 2556 | 2.2014          |
| 2.2327        | 10.0  | 2840 | 2.1630          |
| 2.0986        | 11.0  | 3124 | 2.1237          |
| 2.0986        | 12.0  | 3408 | 2.0577          |
| 2.0           | 13.0  | 3692 | 2.0044          |
| 2.0           | 14.0  | 3976 | 2.0466          |
| 1.9237        | 15.0  | 4260 | 1.9496          |
| 1.8744        | 16.0  | 4544 | 1.9517          |
| 1.8744        | 17.0  | 4828 | 1.9466          |
| 1.8342        | 18.0  | 5112 | 1.8942          |
| 1.8342        | 19.0  | 5396 | 1.9457          |
| 1.7994        | 20.0  | 5680 | 1.9262          |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "mlm-20230503-indobert-base-p2-002", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

mlm-20230503-indobert-base-p2-002
=================================


This model is a fine-tuned version of indobenchmark/indobert-base-p2 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.9160


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3