|
--- |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- indonlu |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: distilled-optimized-indobert-classification |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: indonlu |
|
type: indonlu |
|
args: smsa |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9 |
|
- name: F1 |
|
type: f1 |
|
value: 0.8994069293432798 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# distilled-optimized-indobert-classification |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the indonlu dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7397 |
|
- Accuracy: 0.9 |
|
- F1: 0.8994 |
|
|
|
## 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: 4.315104717136378e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 33 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 9 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
|
| 0.128 | 1.0 | 688 | 0.8535 | 0.8913 | 0.8917 | |
|
| 0.1475 | 2.0 | 1376 | 0.9171 | 0.8913 | 0.8913 | |
|
| 0.0997 | 3.0 | 2064 | 0.7799 | 0.8960 | 0.8951 | |
|
| 0.0791 | 4.0 | 2752 | 0.7179 | 0.9032 | 0.9023 | |
|
| 0.0577 | 5.0 | 3440 | 0.6908 | 0.9063 | 0.9055 | |
|
| 0.0406 | 6.0 | 4128 | 0.7613 | 0.8992 | 0.8986 | |
|
| 0.0275 | 7.0 | 4816 | 0.7502 | 0.8992 | 0.8989 | |
|
| 0.023 | 8.0 | 5504 | 0.7408 | 0.8976 | 0.8969 | |
|
| 0.0169 | 9.0 | 6192 | 0.7397 | 0.9 | 0.8994 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.18.0 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.12.1 |
|
|
