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# mlm-20230405-002-3

This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5498

## 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   | 261  | 4.6412          |
| 5.1283        | 2.0   | 522  | 3.9156          |
| 5.1283        | 3.0   | 783  | 3.5559          |
| 3.6421        | 4.0   | 1044 | 3.2988          |
| 3.6421        | 5.0   | 1305 | 3.1616          |
| 3.1926        | 6.0   | 1566 | 3.0551          |
| 3.1926        | 7.0   | 1827 | 2.9465          |
| 2.9067        | 8.0   | 2088 | 2.9188          |
| 2.9067        | 9.0   | 2349 | 2.8833          |
| 2.7245        | 10.0  | 2610 | 2.7818          |
| 2.7245        | 11.0  | 2871 | 2.6725          |
| 2.5946        | 12.0  | 3132 | 2.7569          |
| 2.5946        | 13.0  | 3393 | 2.6592          |
| 2.5204        | 14.0  | 3654 | 2.6180          |
| 2.5204        | 15.0  | 3915 | 2.6305          |
| 2.4173        | 16.0  | 4176 | 2.6301          |
| 2.4173        | 17.0  | 4437 | 2.5706          |
| 2.3905        | 18.0  | 4698 | 2.5595          |
| 2.3905        | 19.0  | 4959 | 2.5339          |
| 2.3455        | 20.0  | 5220 | 2.5753          |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "mlm-20230405-002-3", "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-20230405-002-3
==================


This model is a fine-tuned version of indobenchmark/indobert-base-p1 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.5498


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 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* 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 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* 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 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* 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 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3