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# test3

This model is a fine-tuned version of [jcblaise/bert-tagalog-base-cased](https://huggingface.co/jcblaise/bert-tagalog-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3960
- Accuracy: 0.8683
- Precision: 0.8316
- Recall: 0.8653
- F1: 0.8481

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 151  | 0.3770          | 0.8431   | 0.8287    | 0.7951 | 0.8115 |
| No log        | 2.0   | 302  | 0.3561          | 0.8528   | 0.7959    | 0.8790 | 0.8354 |
| No log        | 3.0   | 453  | 0.3425          | 0.8647   | 0.8636    | 0.8094 | 0.8356 |
| 0.3579        | 4.0   | 604  | 0.3541          | 0.8615   | 0.8090    | 0.8824 | 0.8441 |
| 0.3579        | 5.0   | 755  | 0.3717          | 0.8611   | 0.8075    | 0.8836 | 0.8438 |
| 0.3579        | 6.0   | 906  | 0.3657          | 0.8691   | 0.8352    | 0.8619 | 0.8483 |
| 0.1703        | 7.0   | 1057 | 0.3826          | 0.8700   | 0.8370    | 0.8619 | 0.8493 |
| 0.1703        | 8.0   | 1208 | 0.3960          | 0.8683   | 0.8316    | 0.8653 | 0.8481 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2

{"license": "gpl-3.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall", "f1"], "model-index": [{"name": "test3", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer license:gpl-3.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #region-us 

test3
=====


This model is a fine-tuned version of jcblaise/bert-tagalog-base-cased on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3960
* Accuracy: 0.8683
* Precision: 0.8316
* Recall: 0.8653
* F1: 0.8481


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: 1e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* Tokenizers 0.13.2