metadata
license: mit
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
model-index:
- name: roberta-base-indonesian-sentiment-analysis-smsa
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: indonlu
type: indonlu
args: smsa
metrics:
- name: Accuracy
type: accuracy
value: 0.9349206349206349
roberta-base-indonesian-sentiment-analysis-smsa
This model is a fine-tuned version of flax-community/indonesian-roberta-base on the indonlu dataset. It achieves the following results on the evaluation set:
- Loss: 0.4252
- Accuracy: 0.9349
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.7582 | 1.0 | 688 | 0.3280 | 0.8786 |
0.3225 | 2.0 | 1376 | 0.2398 | 0.9206 |
0.2057 | 3.0 | 2064 | 0.2574 | 0.9230 |
0.1642 | 4.0 | 2752 | 0.2820 | 0.9302 |
0.1266 | 5.0 | 3440 | 0.3344 | 0.9317 |
0.0608 | 6.0 | 4128 | 0.3543 | 0.9341 |
0.058 | 7.0 | 4816 | 0.4252 | 0.9349 |
0.0315 | 8.0 | 5504 | 0.4736 | 0.9310 |
0.0166 | 9.0 | 6192 | 0.4649 | 0.9349 |
0.0143 | 10.0 | 6880 | 0.4648 | 0.9341 |
Framework versions
- Transformers 4.14.1
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3