---
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: 1.0515
- Exact Match: 65.9686
- F1: 71.4684

## 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      |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
| 6.1822        | 0.49  | 36   | 2.5004          | 49.8691     | 49.8691 |
| 3.6893        | 0.98  | 72   | 1.9896          | 49.8691     | 49.8691 |
| 2.2116        | 1.48  | 108  | 1.8516          | 49.2147     | 49.7070 |
| 2.2116        | 1.97  | 144  | 1.7367          | 50.1309     | 52.0399 |
| 1.9945        | 2.46  | 180  | 1.5956          | 51.7016     | 56.3444 |
| 1.7443        | 2.95  | 216  | 1.4508          | 54.9738     | 59.4030 |
| 1.5782        | 3.45  | 252  | 1.3234          | 59.9476     | 65.0857 |
| 1.5782        | 3.94  | 288  | 1.2652          | 58.1152     | 63.9949 |
| 1.4004        | 4.44  | 324  | 1.1784          | 62.0419     | 67.5268 |
| 1.241         | 4.93  | 360  | 1.1573          | 60.4712     | 66.5284 |
| 1.241         | 5.42  | 396  | 1.1217          | 62.4346     | 67.8923 |
| 1.1603        | 5.91  | 432  | 1.0997          | 63.3508     | 68.7351 |
| 1.0849        | 6.41  | 468  | 1.0832          | 64.3979     | 69.5781 |
| 1.0209        | 6.9   | 504  | 1.0773          | 64.0052     | 69.3072 |
| 1.0209        | 7.4   | 540  | 1.0500          | 65.0524     | 70.4355 |
| 0.9802        | 7.89  | 576  | 1.0644          | 65.3141     | 70.7507 |
| 0.9536        | 8.38  | 612  | 1.0516          | 65.5759     | 70.9704 |
| 0.9536        | 8.87  | 648  | 1.0395          | 65.4450     | 71.2117 |
| 0.9319        | 9.37  | 684  | 1.0411          | 65.8377     | 71.3692 |
| 0.9091        | 9.86  | 720  | 1.0515          | 65.9686     | 71.4684 |


### Framework versions

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