|
--- |
|
license: apache-2.0 |
|
base_model: AptaArkana/indonesian-emotion-distilbert-base-cased-finetuned |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
model-index: |
|
- name: DistilBERT-Rating-Prediction |
|
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. --> |
|
|
|
# DistilBERT-Rating-Prediction |
|
|
|
This model is a fine-tuned version of [AptaArkana/indonesian-emotion-distilbert-base-cased-finetuned](https://huggingface.co/AptaArkana/indonesian-emotion-distilbert-base-cased-finetuned) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9357 |
|
- F1: 0.3927 |
|
|
|
## 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: 5e-06 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.15 |
|
- num_epochs: 10 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 0.5927 | 1.0 | 91 | 0.8094 | 0.3878 | |
|
| 0.4851 | 2.0 | 182 | 0.8268 | 0.3846 | |
|
| 0.2956 | 3.0 | 273 | 0.8444 | 0.3809 | |
|
| 0.1669 | 4.0 | 364 | 0.8558 | 0.3738 | |
|
| 0.2344 | 5.0 | 455 | 0.8772 | 0.3688 | |
|
| 0.0776 | 6.0 | 546 | 0.8992 | 0.3746 | |
|
| 0.2512 | 7.0 | 637 | 0.9313 | 0.3781 | |
|
| 0.1181 | 8.0 | 728 | 0.9292 | 0.3796 | |
|
| 0.2482 | 9.0 | 819 | 0.9284 | 0.3889 | |
|
| 0.6544 | 10.0 | 910 | 0.9357 | 0.3927 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.1 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.15.2 |
|
|
