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--- |
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base_model: csebuetnlp/banglabert |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: banglabert-MLTC-BB1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# banglabert-MLTC-BB1 |
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This model is a fine-tuned version of [csebuetnlp/banglabert](https://huggingface.co/csebuetnlp/banglabert) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4011 |
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- F1: 0.8602 |
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- Roc Auc: 0.8579 |
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- Accuracy: 0.5758 |
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- Hamming Loss: 0.1420 |
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- Jaccard Score: 0.7547 |
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- Zero One Loss: 0.4242 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | Hamming Loss | Jaccard Score | Zero One Loss | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:------------:|:-------------:|:-------------:| |
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| 0.2462 | 1.0 | 49 | 0.3759 | 0.8582 | 0.8534 | 0.5758 | 0.1465 | 0.7516 | 0.4242 | |
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| 0.2099 | 2.0 | 98 | 0.3534 | 0.8656 | 0.8650 | 0.5964 | 0.1350 | 0.7630 | 0.4036 | |
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| 0.2067 | 3.0 | 147 | 0.3660 | 0.8613 | 0.8599 | 0.5861 | 0.1401 | 0.7564 | 0.4139 | |
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| 0.168 | 4.0 | 196 | 0.3672 | 0.8582 | 0.8567 | 0.5835 | 0.1433 | 0.7517 | 0.4165 | |
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| 0.1425 | 5.0 | 245 | 0.3745 | 0.8555 | 0.8547 | 0.5656 | 0.1452 | 0.7475 | 0.4344 | |
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| 0.1545 | 6.0 | 294 | 0.3894 | 0.8544 | 0.8522 | 0.5578 | 0.1478 | 0.7459 | 0.4422 | |
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| 0.1115 | 7.0 | 343 | 0.3995 | 0.8579 | 0.8560 | 0.5681 | 0.1440 | 0.7511 | 0.4319 | |
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| 0.1158 | 8.0 | 392 | 0.4054 | 0.8580 | 0.8554 | 0.5681 | 0.1446 | 0.7514 | 0.4319 | |
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| 0.1055 | 9.0 | 441 | 0.3996 | 0.8575 | 0.8560 | 0.5681 | 0.1440 | 0.7506 | 0.4319 | |
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| 0.105 | 10.0 | 490 | 0.4011 | 0.8602 | 0.8579 | 0.5758 | 0.1420 | 0.7547 | 0.4242 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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