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# test2

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: 0.4185
- Accuracy: 0.8669
- Precision: 0.8249
- Recall: 0.8612
- F1: 0.8426

## 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   | 172  | 0.3674          | 0.8444   | 0.8014    | 0.8295 | 0.8152 |
| No log        | 2.0   | 344  | 0.3508          | 0.8542   | 0.8235    | 0.8243 | 0.8239 |
| 0.2992        | 3.0   | 516  | 0.3643          | 0.8564   | 0.8596    | 0.7803 | 0.8181 |
| 0.2992        | 4.0   | 688  | 0.3639          | 0.8622   | 0.8155    | 0.8620 | 0.8381 |
| 0.2992        | 5.0   | 860  | 0.3803          | 0.864    | 0.8316    | 0.8418 | 0.8367 |
| 0.1733        | 6.0   | 1032 | 0.3969          | 0.8702   | 0.8352    | 0.8550 | 0.8450 |
| 0.1733        | 7.0   | 1204 | 0.4185          | 0.8669   | 0.8249    | 0.8612 | 0.8426 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Tokenizers 0.13.2
{"license": "gpl-3.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall", "f1"], "pipeline_tag": "text-classification", "model-index": [{"name": "test2", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer license:gpl-3.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 

test2
=====


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: 0.4185
* Accuracy: 0.8669
* Precision: 0.8249
* Recall: 0.8612
* F1: 0.8426


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
* 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
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #has_space #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
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #has_space #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
* Tokenizers 0.13.2