| --- |
| license: mit |
| base_model: Ransaka/sinhala-bert-medium-v2 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: SentimentClassifier.si |
| results: [] |
| language: |
| - si |
| pipeline_tag: text-classification |
| --- |
| |
| <!-- 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. --> |
|
|
| # SentimentClassifier.si |
|
|
| This model is a fine-tuned version of [Ransaka/sinhala-bert-medium-v2](https://huggingface.co/Ransaka/sinhala-bert-medium-v2) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2358 |
| - F1: 0.8877 |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| Labels |
| ```plaintext |
| NEGATIVE: 1 |
| POSITIVE: 0 |
| ``` |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 0.0002 |
| - 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 |
| - training_steps: 1000 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 0.4053 | 0.08 | 100 | 0.2802 | 0.8677 | |
| | 0.3768 | 0.16 | 200 | 0.3123 | 0.8616 | |
| | 0.3334 | 0.24 | 300 | 0.2810 | 0.8732 | |
| | 0.2906 | 0.32 | 400 | 0.2554 | 0.8779 | |
| | 0.3027 | 0.4 | 500 | 0.2595 | 0.8836 | |
| | 0.2612 | 0.48 | 600 | 0.2797 | 0.8592 | |
| | 0.2568 | 0.56 | 700 | 0.2474 | 0.8785 | |
| | 0.2325 | 0.64 | 800 | 0.2546 | 0.8816 | |
| | 0.2272 | 0.72 | 900 | 0.2424 | 0.8878 | |
| | 0.2331 | 0.8 | 1000 | 0.2358 | 0.8877 | |
|
|
| Model performance on validation dataset |
|
|
| ```plaintext |
| precision recall f1-score support |
| |
| 0 0.95 0.92 0.93 6943 |
| 1 0.82 0.88 0.84 2913 |
| |
| accuracy 0.90 9856 |
| macro avg 0.88 0.90 0.89 9856 |
| weighted avg 0.91 0.90 0.91 9856 |
| ``` |
|
|
| <img |
| src="https://cdn-uploads.huggingface.co/production/uploads/60f2e10dadf471cbdf8bb661/Yi9TbdOF6CoMfKk40Bcvu.png" |
| alt="Confusion Matrix on Validation Data" |
| width="300"> |
|
|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.15.0 |
| - Tokenizers 0.15.0 |
