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# fine-tuned-DatasetQAS-Squad-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: 1.5175
- Exact Match: 48.5572
- F1: 65.0249

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 128
- 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      |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
| 2.0255        | 0.5   | 463  | 1.8578          | 38.8323     | 53.2780 |
| 1.8396        | 1.0   | 926  | 1.6659          | 43.2069     | 59.4121 |
| 1.6258        | 1.5   | 1389 | 1.5971          | 45.0913     | 61.6718 |
| 1.5939        | 2.0   | 1852 | 1.5523          | 46.3447     | 62.8415 |
| 1.4904        | 2.5   | 2315 | 1.5345          | 46.9589     | 63.7167 |
| 1.5015        | 3.0   | 2778 | 1.5060          | 47.4889     | 64.4261 |
| 1.3787        | 3.5   | 3241 | 1.5092          | 47.7833     | 64.2215 |
| 1.3629        | 4.0   | 3704 | 1.4885          | 48.0273     | 64.6938 |
| 1.3229        | 4.5   | 4167 | 1.5174          | 48.2712     | 64.9266 |
| 1.2848        | 5.0   | 4630 | 1.4942          | 48.4899     | 64.9576 |
| 1.2703        | 5.5   | 5093 | 1.5074          | 48.5657     | 65.0539 |
| 1.2104        | 6.0   | 5556 | 1.5112          | 48.1114     | 64.6513 |
| 1.1775        | 6.5   | 6019 | 1.5004          | 48.1534     | 64.8169 |
| 1.2303        | 7.0   | 6482 | 1.4956          | 48.4647     | 65.0723 |
| 1.1673        | 7.5   | 6945 | 1.5151          | 48.5825     | 65.0862 |
| 1.1771        | 8.0   | 7408 | 1.5057          | 48.5657     | 65.0123 |
| 1.1172        | 8.5   | 7871 | 1.5286          | 48.4311     | 64.7537 |
| 1.1282        | 9.0   | 8334 | 1.5175          | 48.5572     | 65.0249 |


### 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-Squad-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-Squad-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: 1.5175
* Exact Match: 48.5572
* F1: 65.0249


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: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 128
* 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: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 128
* 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: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 128
* 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