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indic-bert-MLTC-BB1
NaeemCSECUET18/indic-bert-MLTC-BB1
indic-bert-MLTC-BB1 is a text classification model from NaeemCSECUET18. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- albert
- Access
- Public
- Created
- Jun 4, 2024
- Updated
- Jun 4, 2024
- SHA
- edf55a1d
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
indic-bert-MLTC-BB1
This model is a fine-tuned version of ai4bharat/indic-bert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5041
- F1: 0.7518
- Roc Auc: 0.7539
- Accuracy: 0.3728
- Hamming Loss: 0.2461
- Jaccard Score: 0.6023
- Zero One Loss: 0.6272
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.6264 | 1.0 | 49 | 0.6551 | 0.6188 | 0.6176 | 0.1028 | 0.3824 | 0.4481 | 0.8972 |
| 0.6024 | 2.0 | 98 | 0.6163 | 0.6967 | 0.6442 | 0.3316 | 0.3554 | 0.5345 | 0.6684 |
| 0.5574 | 3.0 | 147 | 0.5932 | 0.7081 | 0.6492 | 0.3548 | 0.3503 | 0.5481 | 0.6452 |
| 0.5267 | 4.0 | 196 | 0.6041 | 0.7105 | 0.6512 | 0.3573 | 0.3483 | 0.5510 | 0.6427 |
| 0.4988 | 5.0 | 245 | 0.5409 | 0.7215 | 0.6822 | 0.3573 | 0.3175 | 0.5644 | 0.6427 |
| 0.4609 | 6.0 | 294 | 0.5189 | 0.7188 | 0.6880 | 0.3419 | 0.3117 | 0.5611 | 0.6581 |
| 0.4214 | 7.0 | 343 | 0.5426 | 0.7423 | 0.7196 | 0.3676 | 0.2802 | 0.5902 | 0.6324 |
| 0.426 | 8.0 | 392 | 0.5119 | 0.7478 | 0.7416 | 0.3702 | 0.2584 | 0.5972 | 0.6298 |
| 0.4034 | 9.0 | 441 | 0.5065 | 0.7526 | 0.7506 | 0.3805 | 0.2494 | 0.6033 | 0.6195 |
| 0.3974 | 10.0 | 490 | 0.5041 | 0.7518 | 0.7539 | 0.3728 | 0.2461 | 0.6023 | 0.6272 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- albert
- License
- mit
- Created
- Jun 4, 2024
- Updated
- Jun 4, 2024