|
--- |
|
license: apache-2.0 |
|
base_model: indolem/indobertweet-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
- f1 |
|
model-index: |
|
- name: indo_sentiment_indobertbdc |
|
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. --> |
|
|
|
# indo_sentiment_indobertbdc |
|
|
|
This model is a fine-tuned version of [indolem/indobertweet-base-uncased](https://huggingface.co/indolem/indobertweet-base-uncased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8227 |
|
- Accuracy: 0.8234 |
|
- Precision: 0.6493 |
|
- Recall: 0.5790 |
|
- F1: 0.6035 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
| 0.9616 | 1.0 | 110 | 0.6410 | 0.8084 | 0.5908 | 0.5401 | 0.5498 | |
|
| 0.5537 | 2.0 | 220 | 0.6940 | 0.7994 | 0.5502 | 0.5731 | 0.5501 | |
|
| 0.311 | 3.0 | 330 | 0.7103 | 0.8104 | 0.6113 | 0.5502 | 0.5690 | |
|
| 0.1748 | 4.0 | 440 | 0.8169 | 0.8174 | 0.6415 | 0.5875 | 0.6008 | |
|
| 0.0996 | 5.0 | 550 | 0.8227 | 0.8234 | 0.6493 | 0.5790 | 0.6035 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.1 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.19.1 |
|
|
