| --- |
| 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 |
| |
