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indic-sentence-bert-nli-hinglish-binary
callmesan/indic-sentence-bert-nli-hinglish-binary
indic-sentence-bert-nli-hinglish-binary is a text classification model from callmesan. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as cc-by-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- cc-by-4.0
- Model type
- bert
- Access
- Public
- Created
- Dec 3, 2024
- Updated
- Dec 3, 2024
- SHA
- 0836d128
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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-sentence-bert-nli-hinglish-binary
This model is a fine-tuned version of l3cube-pune/indic-sentence-bert-nli on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5934
- Accuracy: 0.6987
- Precision: 0.6929
- Recall: 0.6155
- F1: 0.6125
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.663 | 0.9709 | 25 | 0.6551 | 0.6376 | 0.3188 | 0.5 | 0.3894 |
| 0.6284 | 1.9806 | 51 | 0.6314 | 0.6676 | 0.7906 | 0.5430 | 0.4785 |
| 0.6266 | 2.9903 | 77 | 0.6725 | 0.5095 | 0.6373 | 0.5975 | 0.4974 |
| 0.6261 | 4.0 | 103 | 0.6008 | 0.7112 | 0.7124 | 0.6307 | 0.6311 |
| 0.6202 | 4.9709 | 128 | 0.6025 | 0.7057 | 0.7005 | 0.6264 | 0.6265 |
| 0.5987 | 5.9806 | 154 | 0.5907 | 0.7112 | 0.7216 | 0.6258 | 0.6236 |
| 0.5856 | 6.9903 | 180 | 0.5818 | 0.7193 | 0.7253 | 0.6404 | 0.6427 |
| 0.5753 | 8.0 | 206 | 0.5804 | 0.7166 | 0.7502 | 0.6252 | 0.6201 |
| 0.5416 | 8.9709 | 231 | 0.5667 | 0.7221 | 0.7424 | 0.6376 | 0.6378 |
| 0.5419 | 9.7087 | 250 | 0.5599 | 0.7330 | 0.7439 | 0.6575 | 0.6632 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- cc-by-4.0
- Created
- Dec 3, 2024
- Updated
- Dec 3, 2024