metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bangla-bert-base-VITD
results: []
language:
- bn
pipeline_tag: text-classification
bangla-bert-base-VITD
This model is a fine-tuned version of sagorsarker/bangla-bert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9621
- Accuracy: 0.7263
- F1 score: 0.7237
Training and evaluation data
banglaVITD is used for training and validation.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 score |
|---|---|---|---|---|---|
| 0.8085 | 1.0 | 169 | 0.7044 | 0.6970 | 0.7005 |
| 0.5263 | 2.0 | 338 | 0.6754 | 0.7211 | 0.7124 |
| 0.3115 | 3.0 | 507 | 0.7353 | 0.7301 | 0.7261 |
| 0.1598 | 4.0 | 676 | 1.0257 | 0.7180 | 0.7156 |
| 0.0906 | 5.0 | 845 | 1.5686 | 0.7030 | 0.7032 |
| 0.0702 | 6.0 | 1014 | 1.5592 | 0.7383 | 0.7307 |
| 0.0166 | 7.0 | 1183 | 1.7670 | 0.7293 | 0.7250 |
| 0.0092 | 8.0 | 1352 | 1.9016 | 0.7135 | 0.7129 |
| 0.0056 | 9.0 | 1521 | 1.9197 | 0.7248 | 0.7216 |
| 0.0018 | 10.0 | 1690 | 1.9621 | 0.7263 | 0.7237 |
Framework versions
Transformers 4.30.2
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3