---
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: 1.0942
- Exact Match: 64.3979
- F1: 69.8535

## 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      |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
| 6.1478        | 0.49  | 36   | 2.4099          | 49.8691     | 49.8691 |
| 3.581         | 0.98  | 72   | 1.9550          | 49.8691     | 49.8691 |
| 2.195         | 1.48  | 108  | 1.8446          | 49.3455     | 49.8564 |
| 2.195         | 1.97  | 144  | 1.7512          | 49.4764     | 51.2613 |
| 2.0071        | 2.46  | 180  | 1.6324          | 49.6073     | 52.3994 |
| 1.8105        | 2.95  | 216  | 1.5278          | 52.7487     | 55.8533 |
| 1.6668        | 3.45  | 252  | 1.3938          | 56.6754     | 60.5142 |
| 1.6668        | 3.94  | 288  | 1.3243          | 56.9372     | 62.8755 |
| 1.4715        | 4.44  | 324  | 1.2475          | 60.6021     | 66.5376 |
| 1.3112        | 4.93  | 360  | 1.2257          | 59.4241     | 65.0059 |
| 1.3112        | 5.42  | 396  | 1.1793          | 60.9948     | 66.2895 |
| 1.2443        | 5.91  | 432  | 1.1485          | 63.4817     | 69.0854 |
| 1.1586        | 6.41  | 468  | 1.1178          | 64.1361     | 69.5844 |
| 1.0895        | 6.9   | 504  | 1.1404          | 63.0890     | 68.6016 |
| 1.0895        | 7.4   | 540  | 1.0862          | 65.7068     | 70.8093 |
| 1.054         | 7.89  | 576  | 1.0959          | 64.7906     | 70.2001 |
| 1.0231        | 8.38  | 612  | 1.1036          | 64.3979     | 69.7053 |
| 1.0231        | 8.87  | 648  | 1.0698          | 65.8377     | 71.1488 |
| 0.9985        | 9.37  | 684  | 1.0777          | 66.0995     | 71.3149 |
| 0.9736        | 9.86  | 720  | 1.0942          | 64.3979     | 69.8535 |


### Framework versions

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