metadata
base_model: csebuetnlp/banglabert
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: banglabert-MLTC-BB1
results: []
banglabert-MLTC-BB1
This model is a fine-tuned version of csebuetnlp/banglabert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3600
- F1: 0.8593
- Roc Auc: 0.8580
- Accuracy: 0.5733
- Hamming Loss: 0.1420
- Jaccard Score: 0.7533
- Zero One Loss: 0.4267
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: 2e-05
- train_batch_size: 24
- eval_batch_size: 24
- 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 | F1 | Roc Auc | Accuracy | Hamming Loss | Jaccard Score | Zero One Loss |
|---|---|---|---|---|---|---|---|---|---|
| 0.3266 | 1.0 | 49 | 0.3574 | 0.8629 | 0.8592 | 0.5810 | 0.1407 | 0.7588 | 0.4190 |
| 0.2635 | 2.0 | 98 | 0.3531 | 0.8645 | 0.8618 | 0.5938 | 0.1382 | 0.7614 | 0.4062 |
| 0.27 | 3.0 | 147 | 0.3520 | 0.8553 | 0.8541 | 0.5835 | 0.1459 | 0.7472 | 0.4165 |
| 0.2254 | 4.0 | 196 | 0.3627 | 0.8622 | 0.8592 | 0.5913 | 0.1407 | 0.7577 | 0.4087 |
| 0.1966 | 5.0 | 245 | 0.3600 | 0.8593 | 0.8580 | 0.5733 | 0.1420 | 0.7533 | 0.4267 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1