banglabert-MLTC-BB1 / README.md
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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: 0.3620
  • F1: 0.8590
  • F1 Weighted: 0.8576
  • Roc Auc: 0.8573
  • Accuracy: 0.5810
  • Hamming Loss: 0.1427
  • Jaccard Score: 0.7528
  • Zero One Loss: 0.4190

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 F1 Weighted Roc Auc Accuracy Hamming Loss Jaccard Score Zero One Loss
0.5572 1.0 49 0.5051 0.8005 0.7870 0.7871 0.4216 0.2127 0.6673 0.5784
0.3995 2.0 98 0.4366 0.8273 0.8258 0.8160 0.5167 0.1838 0.7055 0.4833
0.3671 3.0 147 0.3832 0.8493 0.8493 0.8451 0.5630 0.1549 0.7380 0.4370
0.3239 4.0 196 0.3671 0.8600 0.8595 0.8573 0.5810 0.1427 0.7544 0.4190
0.2786 5.0 245 0.3593 0.8573 0.8557 0.8541 0.5784 0.1459 0.7503 0.4216
0.2783 6.0 294 0.3608 0.8530 0.8509 0.8502 0.5733 0.1497 0.7437 0.4267
0.2247 7.0 343 0.3576 0.8579 0.8564 0.8573 0.5758 0.1427 0.7511 0.4242
0.2354 8.0 392 0.3631 0.8591 0.8579 0.8560 0.5861 0.1440 0.7530 0.4139
0.2517 9.0 441 0.3630 0.8553 0.8541 0.8534 0.5758 0.1465 0.7472 0.4242
0.223 10.0 490 0.3620 0.8590 0.8576 0.8573 0.5810 0.1427 0.7528 0.4190

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.1.2
  • Datasets 2.19.1
  • Tokenizers 0.19.1