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# Indobert-QA-finetuned-squad

This model is a fine-tuned version of [Rifky/Indobert-QA](https://huggingface.co/Rifky/Indobert-QA) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 15.2477

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 1.1181        | 1.0   | 5510   | 4.8523          |
| 0.9746        | 2.0   | 11020  | 5.4560          |
| 0.8135        | 3.0   | 16530  | 5.7017          |
| 0.6964        | 4.0   | 22040  | 6.2898          |
| 0.6052        | 5.0   | 27550  | 6.0962          |
| 0.512         | 6.0   | 33060  | 6.4996          |
| 0.4303        | 7.0   | 38570  | 6.9570          |
| 0.3532        | 8.0   | 44080  | 7.4206          |
| 0.3199        | 9.0   | 49590  | 7.4004          |
| 0.4247        | 10.0  | 55100  | 6.9846          |
| 0.3641        | 11.0  | 60610  | 6.8940          |
| 0.3277        | 12.0  | 66120  | 7.0796          |
| 0.2899        | 13.0  | 71630  | 7.4511          |
| 0.2794        | 14.0  | 77140  | 7.2660          |
| 0.2496        | 15.0  | 82650  | 7.9774          |
| 0.2299        | 16.0  | 88160  | 7.6985          |
| 0.2082        | 17.0  | 93670  | 7.8321          |
| 0.1975        | 18.0  | 99180  | 8.1735          |
| 0.1784        | 19.0  | 104690 | 8.5620          |
| 0.1675        | 20.0  | 110200 | 8.7616          |
| 0.1613        | 21.0  | 115710 | 8.8350          |
| 0.1484        | 22.0  | 121220 | 8.9582          |
| 0.1482        | 23.0  | 126730 | 9.0406          |
| 0.1381        | 24.0  | 132240 | 8.9652          |
| 0.1411        | 25.0  | 137750 | 9.4613          |
| 0.1236        | 26.0  | 143260 | 9.6738          |
| 0.1216        | 27.0  | 148770 | 9.8708          |
| 0.1192        | 28.0  | 154280 | 10.3220         |
| 0.12          | 29.0  | 159790 | 10.0470         |
| 0.1041        | 30.0  | 165300 | 10.6753         |
| 0.1055        | 31.0  | 170810 | 10.2775         |
| 0.1083        | 32.0  | 176320 | 10.4515         |
| 0.0924        | 33.0  | 181830 | 10.2080         |
| 0.0959        | 34.0  | 187340 | 10.8958         |
| 0.0978        | 35.0  | 192850 | 10.8256         |
| 0.0865        | 36.0  | 198360 | 11.6631         |
| 0.0825        | 37.0  | 203870 | 11.9017         |
| 0.0807        | 38.0  | 209380 | 11.4407         |
| 0.0674        | 39.0  | 214890 | 11.5917         |
| 0.0809        | 40.0  | 220400 | 11.4535         |
| 0.0708        | 41.0  | 225910 | 12.1592         |
| 0.0778        | 42.0  | 231420 | 12.0278         |
| 0.0726        | 43.0  | 236930 | 11.7701         |
| 0.0627        | 44.0  | 242440 | 12.2976         |
| 0.0681        | 45.0  | 247950 | 12.7727         |
| 0.0672        | 46.0  | 253460 | 12.8623         |
| 0.0608        | 47.0  | 258970 | 12.9669         |
| 0.067         | 48.0  | 264480 | 13.4741         |
| 0.0625        | 49.0  | 269990 | 13.6245         |
| 0.0585        | 50.0  | 275500 | 13.4891         |
| 0.0568        | 51.0  | 281010 | 13.4374         |
| 0.0583        | 52.0  | 286520 | 12.8947         |
| 0.0467        | 53.0  | 292030 | 13.6060         |
| 0.0416        | 54.0  | 297540 | 14.3267         |
| 0.0504        | 55.0  | 303050 | 13.7715         |
| 0.0431        | 56.0  | 308560 | 13.8461         |
| 0.0412        | 57.0  | 314070 | 13.7060         |
| 0.0383        | 58.0  | 319580 | 14.3548         |
| 0.0327        | 59.0  | 325090 | 14.4535         |
| 0.0448        | 60.0  | 330600 | 14.2505         |
| 0.0409        | 61.0  | 336110 | 13.8177         |
| 0.0332        | 62.0  | 341620 | 13.0098         |
| 0.0345        | 63.0  | 347130 | 13.8678         |
| 0.0267        | 64.0  | 352640 | 14.3916         |
| 0.0302        | 65.0  | 358150 | 14.1668         |
| 0.0292        | 66.0  | 363660 | 13.6313         |
| 0.0302        | 67.0  | 369170 | 14.1120         |
| 0.0265        | 68.0  | 374680 | 15.0709         |
| 0.0276        | 69.0  | 380190 | 14.6093         |
| 0.0223        | 70.0  | 385700 | 15.0999         |
| 0.0306        | 71.0  | 391210 | 15.1224         |
| 0.0281        | 72.0  | 396720 | 15.5029         |
| 0.019         | 73.0  | 402230 | 15.3474         |
| 0.02          | 74.0  | 407740 | 14.7976         |
| 0.018         | 75.0  | 413250 | 15.3104         |
| 0.0184        | 76.0  | 418760 | 15.3137         |
| 0.0171        | 77.0  | 424270 | 14.8188         |
| 0.0164        | 78.0  | 429780 | 15.4378         |
| 0.0165        | 79.0  | 435290 | 15.1186         |
| 0.0168        | 80.0  | 440800 | 14.7998         |
| 0.0115        | 81.0  | 446310 | 14.4591         |
| 0.0138        | 82.0  | 451820 | 15.2517         |
| 0.0117        | 83.0  | 457330 | 14.7899         |
| 0.0118        | 84.0  | 462840 | 15.5304         |
| 0.0119        | 85.0  | 468350 | 14.6794         |
| 0.0134        | 86.0  | 473860 | 14.5271         |
| 0.0076        | 87.0  | 479370 | 15.7098         |
| 0.0076        | 88.0  | 484880 | 14.2286         |
| 0.01          | 89.0  | 490390 | 15.2608         |
| 0.0094        | 90.0  | 495900 | 14.9055         |
| 0.0069        | 91.0  | 501410 | 14.8540         |
| 0.0082        | 92.0  | 506920 | 15.2562         |
| 0.0068        | 93.0  | 512430 | 14.9342         |
| 0.0047        | 94.0  | 517940 | 15.3755         |
| 0.0062        | 95.0  | 523450 | 15.2753         |
| 0.0046        | 96.0  | 528960 | 15.0191         |
| 0.0057        | 97.0  | 534470 | 14.9508         |
| 0.0033        | 98.0  | 539980 | 15.4440         |
| 0.0045        | 99.0  | 545490 | 15.4171         |
| 0.0048        | 100.0 | 551000 | 15.2477         |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu102
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "Indobert-QA-finetuned-squad", "results": []}]}
transformers pytorch tensorboard bert question-answering generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

Indobert-QA-finetuned-squad
===========================


This model is a fine-tuned version of Rifky/Indobert-QA on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 15.2477


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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100


### Training results



### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu102
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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
* num\_epochs: 100 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu102
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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
* num\_epochs: 100 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu102
* Datasets 2.2.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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
* num\_epochs: 100### Training results### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu102
* Datasets 2.2.2
* Tokenizers 0.12.1