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# lm-001

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: 2.6661

## 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   | 206  | 4.9168          |
| No log        | 2.0   | 412  | 4.1508          |
| 5.0799        | 3.0   | 618  | 3.7045          |
| 5.0799        | 4.0   | 824  | 3.5202          |
| 3.5959        | 5.0   | 1030 | 3.3053          |
| 3.5959        | 6.0   | 1236 | 3.2019          |
| 3.5959        | 7.0   | 1442 | 3.1049          |
| 3.1377        | 8.0   | 1648 | 2.9601          |
| 3.1377        | 9.0   | 1854 | 2.9142          |
| 2.8985        | 10.0  | 2060 | 2.8329          |
| 2.8985        | 11.0  | 2266 | 2.8186          |
| 2.8985        | 12.0  | 2472 | 2.8022          |
| 2.6988        | 13.0  | 2678 | 2.7455          |
| 2.6988        | 14.0  | 2884 | 2.7193          |
| 2.5927        | 15.0  | 3090 | 2.6942          |
| 2.5927        | 16.0  | 3296 | 2.6657          |
| 2.5015        | 17.0  | 3502 | 2.6681          |
| 2.5015        | 18.0  | 3708 | 2.6694          |
| 2.5015        | 19.0  | 3914 | 2.6911          |
| 2.4554        | 20.0  | 4120 | 2.6235          |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "lm-001", "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 

lm-001
======


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: 2.6661


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 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2



### 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 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
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 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
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 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2