
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# indobertweet-finetuned-ijelid

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5301
- Precision: 0.9246
- Recall: 0.9344
- F1: 0.9293
- Accuracy: 0.9513

## 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: 128
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 49   | 0.5141          | 0.9216    | 0.9326 | 0.9268 | 0.9508   |
| No log        | 2.0   | 98   | 0.5187          | 0.9222    | 0.9356 | 0.9285 | 0.9512   |
| No log        | 3.0   | 147  | 0.5307          | 0.9256    | 0.9341 | 0.9296 | 0.9516   |
| No log        | 4.0   | 196  | 0.5307          | 0.9251    | 0.9343 | 0.9295 | 0.9512   |
| No log        | 5.0   | 245  | 0.5301          | 0.9246    | 0.9344 | 0.9293 | 0.9513   |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.12.1+cu102
- Datasets 2.5.1
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "widget": [{"text": "Productnya bagus bgt guys, nek bales chat cepet tur pelayanane apik."}], "model-index": [{"name": "indobertweet-finetuned-ijelid", "results": []}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

indobertweet-finetuned-ijelid
=============================


This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5301
* Precision: 0.9246
* Recall: 0.9344
* F1: 0.9293
* Accuracy: 0.9513


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: 128
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu102
* Datasets 2.5.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 128
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu102
* Datasets 2.5.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 128
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu102
* Datasets 2.5.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 128
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5### Training results### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu102
* Datasets 2.5.1
* Tokenizers 0.12.1