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# fine-tuned-DatasetQAS-TYDI-QA-ID-with-indobert-large-p2-with-ITTL-with-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: 1.2003
- Exact Match: 60.2113
- F1: 73.9948

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 64
- 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      |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
| 6.2316        | 0.5   | 19   | 3.5321          | 11.9718     | 21.8197 |
| 6.2316        | 0.99  | 38   | 2.6566          | 19.1901     | 31.9985 |
| 3.5132        | 1.5   | 57   | 2.1442          | 27.2887     | 40.7031 |
| 3.5132        | 1.99  | 76   | 1.6755          | 41.5493     | 53.9850 |
| 3.5132        | 2.5   | 95   | 1.4228          | 48.2394     | 61.2829 |
| 1.845         | 2.99  | 114  | 1.2882          | 52.8169     | 66.2197 |
| 1.845         | 3.5   | 133  | 1.2352          | 54.7535     | 68.3725 |
| 1.2542        | 3.99  | 152  | 1.2033          | 56.6901     | 70.5019 |
| 1.2542        | 4.5   | 171  | 1.2117          | 57.9225     | 72.0740 |
| 1.2542        | 4.99  | 190  | 1.1748          | 58.4507     | 71.9264 |
| 0.9877        | 5.5   | 209  | 1.1763          | 58.8028     | 72.2772 |
| 0.9877        | 5.99  | 228  | 1.1827          | 59.5070     | 73.5652 |
| 0.9877        | 6.5   | 247  | 1.1789          | 59.8592     | 73.2748 |
| 0.8293        | 6.99  | 266  | 1.1835          | 60.0352     | 73.4695 |
| 0.8293        | 7.5   | 285  | 1.1669          | 59.8592     | 73.7145 |
| 0.7663        | 7.99  | 304  | 1.1912          | 60.3873     | 74.3001 |
| 0.7663        | 8.5   | 323  | 1.1828          | 60.2113     | 74.1533 |
| 0.7663        | 8.99  | 342  | 1.2046          | 60.3873     | 74.0424 |
| 0.7068        | 9.5   | 361  | 1.2003          | 60.2113     | 73.9948 |


### 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-TYDI-QA-ID-with-indobert-large-p2-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-TYDI-QA-ID-with-indobert-large-p2-with-ITTL-with-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: 1.2003
* Exact Match: 60.2113
* F1: 73.9948


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: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 64
* 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: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 64
* 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: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 64
* 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