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# fine-tuned-DatasetQAS-TYDI-QA-ID-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: 1.3132
- Exact Match: 53.2628
- F1: 68.3641

## 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      |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
| 6.3129        | 0.5   | 19   | 3.9006          | 5.6437      | 16.4748 |
| 6.3129        | 1.0   | 38   | 2.8272          | 17.1076     | 30.0839 |
| 3.8917        | 1.5   | 57   | 2.4681          | 18.8713     | 32.8962 |
| 3.8917        | 2.0   | 76   | 2.2891          | 25.3968     | 38.0874 |
| 3.8917        | 2.5   | 95   | 2.1835          | 26.9841     | 39.5053 |
| 2.3963        | 3.0   | 114  | 2.0885          | 28.5714     | 42.0243 |
| 2.3963        | 3.5   | 133  | 1.9971          | 32.4515     | 45.4085 |
| 2.112         | 4.0   | 152  | 1.9124          | 34.3915     | 48.2893 |
| 2.112         | 4.5   | 171  | 1.8358          | 37.0370     | 50.6492 |
| 2.112         | 5.0   | 190  | 1.7545          | 40.7407     | 54.7031 |
| 1.8205        | 5.5   | 209  | 1.6432          | 44.4444     | 58.2669 |
| 1.8205        | 6.0   | 228  | 1.5589          | 46.9136     | 60.8052 |
| 1.8205        | 6.5   | 247  | 1.4861          | 48.1481     | 62.5185 |
| 1.573         | 7.0   | 266  | 1.4381          | 49.7354     | 64.1985 |
| 1.573         | 7.5   | 285  | 1.3944          | 51.6755     | 66.0223 |
| 1.387         | 8.0   | 304  | 1.3534          | 53.2628     | 67.6841 |
| 1.387         | 8.5   | 323  | 1.3384          | 53.0864     | 67.8619 |
| 1.387         | 9.0   | 342  | 1.3344          | 52.9101     | 68.0618 |
| 1.2998        | 9.5   | 361  | 1.3182          | 53.2628     | 68.4149 |
| 1.2998        | 10.0  | 380  | 1.3132          | 53.2628     | 68.3641 |


### 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-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-TYDI-QA-ID-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: 1.3132
* Exact Match: 53.2628
* F1: 68.3641


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