---
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
language:
- ind
datasets:
- GEM/indonlg
metrics:
- f1
model-index:
- name: IndoNanoT5-base-TyDiQA
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: indonlg
      type: indonlg
      config: question_answering
      split: test
      args: question_answering
    metrics:
    - name: F1
      type: f1
      value: 72.19688326266134
    - name: EM
      type: em
      value: 58.9474
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# LazarusNLP/IndoNanoT5-base-TyDiQA

This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the indonlg dataset.
It achieves the following results on the evaluation set:
- Exact: 58.9474
- F1: 72.1969
- Total: 855
- Hasans Exact: 58.9474
- Hasans F1: 72.1969
- Hasans Total: 855
- Best Exact: 58.9474
- Best Exact Thresh: 0.0
- Best F1: 72.1969
- Best F1 Thresh: 0.0
- Loss: 0.1283

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Exact   | F1      | Total | Hasans Exact | Hasans F1 | Hasans Total | Best Exact | Best Exact Thresh | Best F1 | Best F1 Thresh | Validation Loss |
|:-------------:|:-----:|:----:|:-------:|:-------:|:-----:|:------------:|:---------:|:------------:|:----------:|:-----------------:|:-------:|:--------------:|:---------------:|
| 1.9173        | 1.0   | 606  | 45.1327 | 63.8499 | 565   | 45.1327      | 63.8499   | 565          | 45.1327    | 0.0               | 63.8499 | 0.0            | 0.1147          |
| 0.1971        | 2.0   | 1212 | 50.4425 | 68.7240 | 565   | 50.4425      | 68.7240   | 565          | 50.4425    | 0.0               | 68.7240 | 0.0            | 0.1025          |
| 0.1475        | 3.0   | 1818 | 53.8053 | 71.0124 | 565   | 53.8053      | 71.0124   | 565          | 53.8053    | 0.0               | 71.0124 | 0.0            | 0.0992          |
| 0.1175        | 4.0   | 2424 | 53.6283 | 71.1353 | 565   | 53.6283      | 71.1353   | 565          | 53.6283    | 0.0               | 71.1353 | 0.0            | 0.1008          |
| 0.0814        | 5.0   | 3030 | 53.4513 | 71.0439 | 565   | 53.4513      | 71.0439   | 565          | 53.4513    | 0.0               | 71.0439 | 0.0            | 0.1040          |
| 0.0665        | 6.0   | 3636 | 54.1593 | 71.5788 | 565   | 54.1593      | 71.5788   | 565          | 54.1593    | 0.0               | 71.5788 | 0.0            | 0.1051          |
| 0.0555        | 7.0   | 4242 | 54.8673 | 72.4372 | 565   | 54.8673      | 72.4372   | 565          | 54.8673    | 0.0               | 72.4372 | 0.0            | 0.1137          |
| 0.0483        | 8.0   | 4848 | 56.2832 | 72.3749 | 565   | 56.2832      | 72.3749   | 565          | 56.2832    | 0.0               | 72.3749 | 0.0            | 0.1188          |
| 0.0416        | 9.0   | 5454 | 55.5752 | 72.2892 | 565   | 55.5752      | 72.2892   | 565          | 55.5752    | 0.0               | 72.2892 | 0.0            | 0.1154          |
| 0.031         | 10.0  | 6060 | 55.0442 | 71.8127 | 565   | 55.0442      | 71.8127   | 565          | 55.0442    | 0.0               | 71.8127 | 0.0            | 0.1312          |
| 0.0278        | 11.0  | 6666 | 55.7522 | 73.4756 | 565   | 55.7522      | 73.4756   | 565          | 55.7522    | 0.0               | 73.4756 | 0.0            | 0.1253          |
| 0.0257        | 12.0  | 7272 | 55.7522 | 73.0958 | 565   | 55.7522      | 73.0958   | 565          | 55.7522    | 0.0               | 73.0958 | 0.0            | 0.1292          |
| 0.023         | 13.0  | 7878 | 56.2832 | 73.3269 | 565   | 56.2832      | 73.3269   | 565          | 56.2832    | 0.0               | 73.3269 | 0.0            | 0.1271          |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu118
- Datasets 2.16.1
- Tokenizers 0.15.1