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# fine-tuned-DatasetQAS-IDK-MRC-with-indobert-base-uncased-with-ITTL-with-freeze-LR-1e-05

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0641
- Exact Match: 65.1832
- F1: 70.4300

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- 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 | Exact Match | F1      |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
| 6.31          | 0.49  | 36   | 2.5380          | 50.0        | 50.0    |
| 3.7784        | 0.98  | 72   | 1.9420          | 49.8691     | 49.8691 |
| 2.192         | 1.48  | 108  | 1.8160          | 48.8220     | 50.2574 |
| 2.192         | 1.97  | 144  | 1.7327          | 48.8220     | 51.7831 |
| 1.9694        | 2.46  | 180  | 1.6016          | 48.9529     | 53.9425 |
| 1.7482        | 2.95  | 216  | 1.4743          | 54.4503     | 58.8011 |
| 1.5835        | 3.45  | 252  | 1.3414          | 57.4607     | 62.1340 |
| 1.5835        | 3.94  | 288  | 1.2884          | 58.2461     | 63.2663 |
| 1.4053        | 4.44  | 324  | 1.2001          | 60.4712     | 65.7454 |
| 1.2521        | 4.93  | 360  | 1.1738          | 60.7330     | 66.8019 |
| 1.2521        | 5.42  | 396  | 1.1551          | 60.8639     | 66.5188 |
| 1.1668        | 5.91  | 432  | 1.1128          | 63.8743     | 68.7421 |
| 1.097         | 6.41  | 468  | 1.0863          | 63.7435     | 69.1933 |
| 1.0251        | 6.9   | 504  | 1.0843          | 63.0890     | 68.4132 |
| 1.0251        | 7.4   | 540  | 1.0507          | 66.3613     | 71.1898 |
| 1.0031        | 7.89  | 576  | 1.0732          | 63.6126     | 68.7281 |
| 0.9616        | 8.38  | 612  | 1.0689          | 65.0524     | 70.2879 |
| 0.9616        | 8.87  | 648  | 1.0376          | 66.2304     | 71.2857 |
| 0.9322        | 9.37  | 684  | 1.0474          | 65.7068     | 70.7885 |
| 0.9227        | 9.86  | 720  | 1.0641          | 65.1832     | 70.4300 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "fine-tuned-DatasetQAS-IDK-MRC-with-indobert-base-uncased-with-ITTL-with-freeze-LR-1e-05", "results": []}]}
transformers pytorch tensorboard bert question-answering generated_from_trainer license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #license-mit #endpoints_compatible #region-us 

fine-tuned-DatasetQAS-IDK-MRC-with-indobert-base-uncased-with-ITTL-with-freeze-LR-1e-05
=======================================================================================


This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.0641
* Exact Match: 65.1832
* F1: 70.4300


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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 128
* 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+cu117
* Datasets 2.2.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 128
* 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+cu117
* Datasets 2.2.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #license-mit #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 128
* 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+cu117
* Datasets 2.2.0
* Tokenizers 0.13.2