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# fine-tuned-DatasetQAS-IDK-MRC-with-indobert-large-p2-with-ITTL-without-freeze-LR-1e-05

This model is a fine-tuned version of [indobenchmark/indobert-large-p2](https://huggingface.co/indobenchmark/indobert-large-p2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2364
- Exact Match: 50.2618
- F1: 57.5214

## 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      |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
| 6.151         | 0.49  | 36   | 2.7223          | 32.5916     | 35.4445 |
| 3.5424        | 0.98  | 72   | 2.0664          | 24.2147     | 31.0371 |
| 2.2082        | 1.48  | 108  | 1.7388          | 28.0105     | 37.2690 |
| 2.2082        | 1.97  | 144  | 1.4742          | 37.0419     | 45.3625 |
| 1.6932        | 2.46  | 180  | 1.3193          | 43.3246     | 51.1270 |
| 1.3154        | 2.95  | 216  | 1.2731          | 46.2042     | 53.5503 |
| 1.1699        | 3.45  | 252  | 1.2327          | 46.4660     | 53.5656 |
| 1.1699        | 3.94  | 288  | 1.1998          | 48.1675     | 55.1907 |
| 1.0749        | 4.44  | 324  | 1.1949          | 51.0471     | 57.7164 |
| 0.9423        | 4.93  | 360  | 1.1855          | 50.6545     | 57.3903 |
| 0.9423        | 5.42  | 396  | 1.1931          | 51.3089     | 58.5981 |
| 0.9036        | 5.91  | 432  | 1.2045          | 50.3927     | 57.7468 |
| 0.8324        | 6.41  | 468  | 1.2363          | 48.2984     | 55.5302 |
| 0.7846        | 6.9   | 504  | 1.2364          | 50.2618     | 57.5214 |


### 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-large-p2-with-ITTL-without-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-large-p2-with-ITTL-without-freeze-LR-1e-05
======================================================================================


This model is a fine-tuned version of indobenchmark/indobert-large-p2 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.2364
* Exact Match: 50.2618
* F1: 57.5214


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