---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: fine-tuned-DatasetQAS-IDK-MRC-with-indobert-base-uncased-with-ITTL-without-freeze-LR-1e-05
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# fine-tuned-DatasetQAS-IDK-MRC-with-indobert-base-uncased-with-ITTL-without-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: 1.0860
- Exact Match: 64.7906
- F1: 70.2020

## 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      |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
| 6.2255        | 0.49  | 36   | 2.4921          | 50.0        | 50.0    |
| 3.6958        | 0.98  | 72   | 1.9696          | 49.6073     | 49.8277 |
| 2.2068        | 1.48  | 108  | 1.8415          | 47.3822     | 48.9302 |
| 2.2068        | 1.97  | 144  | 1.7148          | 48.1675     | 51.1818 |
| 1.9768        | 2.46  | 180  | 1.5553          | 51.8325     | 56.0847 |
| 1.7318        | 2.95  | 216  | 1.4373          | 55.1047     | 59.8473 |
| 1.5469        | 3.45  | 252  | 1.2970          | 58.3770     | 63.3911 |
| 1.5469        | 3.94  | 288  | 1.2882          | 58.9005     | 64.0631 |
| 1.3771        | 4.44  | 324  | 1.2048          | 62.0419     | 66.6696 |
| 1.2296        | 4.93  | 360  | 1.1860          | 61.7801     | 66.8504 |
| 1.2296        | 5.42  | 396  | 1.1807          | 60.3403     | 65.5550 |
| 1.1715        | 5.91  | 432  | 1.1330          | 62.6963     | 67.5995 |
| 1.0833        | 6.41  | 468  | 1.1292          | 62.8272     | 67.7732 |
| 1.025         | 6.9   | 504  | 1.1256          | 63.3508     | 68.7945 |
| 1.025         | 7.4   | 540  | 1.0740          | 64.5288     | 69.8302 |
| 1.0033        | 7.89  | 576  | 1.0828          | 64.5288     | 69.8559 |
| 0.9603        | 8.38  | 612  | 1.0870          | 63.7435     | 69.1867 |
| 0.9603        | 8.87  | 648  | 1.0655          | 65.9686     | 70.8956 |
| 0.94          | 9.37  | 684  | 1.0717          | 65.3141     | 70.5016 |
| 0.9259        | 9.86  | 720  | 1.0860          | 64.7906     | 70.2020 |


### Framework versions

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