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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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