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Paraphrase_indicBERT_onfull_FT1
Abhi964/Paraphrase_indicBERT_onfull_FT1
Paraphrase_indicBERT_onfull_FT1 is a text classification model from Abhi964. 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
- Mar 8, 2025
- Updated
- Mar 8, 2025
- SHA
- f944c673
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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. -->
Paraphrase_indicBERT_onfull_FT1
This model is a fine-tuned version of ai4bharat/indic-bert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4705
- Accuracy: 0.788
- F1: 0.7873
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: 3.492964437401573e-05
- train_batch_size: 8
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6519 | 1.0 | 625 | 0.6043 | 0.682 | 0.6765 |
| 0.5239 | 2.0 | 1250 | 0.7503 | 0.6875 | 0.6830 |
| 0.5193 | 3.0 | 1875 | 0.5210 | 0.764 | 0.7636 |
| 0.5727 | 4.0 | 2500 | 0.4705 | 0.788 | 0.7873 |
| 0.4156 | 5.0 | 3125 | 0.6685 | 0.786 | 0.7860 |
| 0.2547 | 6.0 | 3750 | 0.8505 | 0.7815 | 0.7810 |
| 0.2266 | 7.0 | 4375 | 1.0129 | 0.774 | 0.7736 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- albert
- License
- mit
- Created
- Mar 8, 2025
- Updated
- Mar 8, 2025