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# roberta-base-indonesian-1.5G-sentiment-analysis-smsa

This model is a fine-tuned version of [cahya/roberta-base-indonesian-1.5G](https://huggingface.co/cahya/roberta-base-indonesian-1.5G) on the indonlu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4294
- Accuracy: 0.9262

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6461        | 1.0   | 688  | 0.2620          | 0.9087   |
| 0.2627        | 2.0   | 1376 | 0.2291          | 0.9151   |
| 0.1784        | 3.0   | 2064 | 0.2891          | 0.9167   |
| 0.1099        | 4.0   | 2752 | 0.3317          | 0.9230   |
| 0.0857        | 5.0   | 3440 | 0.4294          | 0.9262   |
| 0.0346        | 6.0   | 4128 | 0.4759          | 0.9246   |
| 0.0221        | 7.0   | 4816 | 0.4946          | 0.9206   |
| 0.006         | 8.0   | 5504 | 0.5823          | 0.9175   |
| 0.0047        | 9.0   | 6192 | 0.5777          | 0.9159   |
| 0.004         | 10.0  | 6880 | 0.5800          | 0.9175   |


### How to use this model in Transformers Library

```python
from transformers import pipeline

pipe = pipeline(
"text-classification",
model="ayameRushia/roberta-base-indonesian-1.5G-sentiment-analysis-smsa"
)

pipe("Terima kasih atas bantuannya ya!")

```

### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3
{"language": ["id"], "tags": ["generated_from_trainer"], "datasets": ["indonlp/indonlu"], "metrics": ["accuracy"], "widget": [{"text": "Entah mengapa saya merasakan ada sesuatu yang janggal di produk ini"}], "model-index": [{"name": "roberta-base-indonesian-1.5G-sentiment-analysis-smsa", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "indonlu", "type": "indonlu", "args": "smsa"}, "metrics": [{"type": "accuracy", "value": 0.9261904761904762, "name": "Accuracy"}]}]}]}
transformers pytorch roberta text-classification generated_from_trainer id dataset:indonlp/indonlu model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #id #dataset-indonlp/indonlu #model-index #autotrain_compatible #endpoints_compatible #region-us 

roberta-base-indonesian-1.5G-sentiment-analysis-smsa
====================================================


This model is a fine-tuned version of cahya/roberta-base-indonesian-1.5G on the indonlu dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4294
* Accuracy: 0.9262


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1500
* num\_epochs: 10


### Training results



### How to use this model in Transformers Library


### Framework versions


* Transformers 4.14.1
* Pytorch 1.10.0+cu111
* Datasets 1.16.1
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1500
* num\_epochs: 10 ### Training results ### How to use this model in Transformers Library ### Framework versions


* Transformers 4.14.1
* Pytorch 1.10.0+cu111
* Datasets 1.16.1
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #id #dataset-indonlp/indonlu #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1500
* num\_epochs: 10 ### Training results ### How to use this model in Transformers Library ### Framework versions


* Transformers 4.14.1
* Pytorch 1.10.0+cu111
* Datasets 1.16.1
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #id #dataset-indonlp/indonlu #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1500
* num\_epochs: 10### Training results### How to use this model in Transformers Library### Framework versions


* Transformers 4.14.1
* Pytorch 1.10.0+cu111
* Datasets 1.16.1
* Tokenizers 0.10.3