File size: 2,047 Bytes
224a078 9712ab7 224a078 9712ab7 224a078 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 |
---
license: mit
base_model: sagorsarker/bangla-bert-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bangla-bert-base-MLTC-BBAU
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. -->
# bangla-bert-base-MLTC-BBAU
This model is a fine-tuned version of [sagorsarker/bangla-bert-base](https://huggingface.co/sagorsarker/bangla-bert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3665
- F1: 0.8465
- F1 Weighted: 0.8455
- Roc Auc: 0.8412
- Accuracy: 0.5424
- Hamming Loss: 0.1587
- Jaccard Score: 0.7338
- Zero One Loss: 0.4576
## 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: 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | F1 Weighted | Roc Auc | Accuracy | Hamming Loss | Jaccard Score | Zero One Loss |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:-------:|:--------:|:------------:|:-------------:|:-------------:|
| 0.4152 | 1.0 | 73 | 0.4083 | 0.8201 | 0.8155 | 0.8181 | 0.4987 | 0.1819 | 0.6950 | 0.5013 |
| 0.3506 | 2.0 | 146 | 0.3671 | 0.8504 | 0.8509 | 0.8496 | 0.5681 | 0.1504 | 0.7397 | 0.4319 |
| 0.2992 | 3.0 | 219 | 0.3665 | 0.8465 | 0.8455 | 0.8412 | 0.5424 | 0.1587 | 0.7338 | 0.4576 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
|