banglabert-MLTC-1
This model is a fine-tuned version of csebuetnlp/banglabert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3669
- F1: 0.8607
- Roc Auc: 0.8579
- Accuracy: 0.5835
- Hamming Loss: 0.1420
- Jaccard Score: 0.7555
- Zero One Loss: 0.4165
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | Hamming Loss | Jaccard Score | Zero One Loss |
---|---|---|---|---|---|---|---|---|---|
0.4242 | 1.0 | 146 | 0.4373 | 0.8248 | 0.8161 | 0.5013 | 0.1838 | 0.7018 | 0.4987 |
0.39 | 2.0 | 292 | 0.3895 | 0.8407 | 0.8400 | 0.5784 | 0.1600 | 0.7252 | 0.4216 |
0.2973 | 3.0 | 438 | 0.3736 | 0.8595 | 0.8547 | 0.5758 | 0.1452 | 0.7535 | 0.4242 |
0.2465 | 4.0 | 584 | 0.3644 | 0.8638 | 0.8605 | 0.5913 | 0.1395 | 0.7602 | 0.4087 |
0.2918 | 5.0 | 730 | 0.3669 | 0.8607 | 0.8579 | 0.5835 | 0.1420 | 0.7555 | 0.4165 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for NaeemCSECUET18/banglabert-MLTC-1
Base model
csebuetnlp/banglabert