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README.md
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---
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library_name: transformers
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license: cc-by-4.0
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base_model: l3cube-pune/indic-sentence-bert-nli
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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- recall
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- f1
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model-index:
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- name: indic-sentence-bert-nli-hinglish-binary
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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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# indic-sentence-bert-nli-hinglish-binary
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This model is a fine-tuned version of [l3cube-pune/indic-sentence-bert-nli](https://huggingface.co/l3cube-pune/indic-sentence-bert-nli) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6151
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- Accuracy: 0.6921
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- Precision: 0.6876
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- Recall: 0.6039
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- F1: 0.5965
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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: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 128
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.664 | 0.9709 | 25 | 0.6561 | 0.6376 | 0.3188 | 0.5 | 0.3894 |
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| 0.6424 | 1.9806 | 51 | 0.6544 | 0.6376 | 0.3188 | 0.5 | 0.3894 |
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| 0.6373 | 2.9903 | 77 | 0.6223 | 0.7139 | 0.7186 | 0.6328 | 0.6334 |
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| 0.622 | 4.0 | 103 | 0.6048 | 0.7139 | 0.7158 | 0.6345 | 0.6357 |
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| 0.594 | 4.8544 | 125 | 0.6002 | 0.7166 | 0.7220 | 0.6366 | 0.6380 |
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### Framework versions
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- Transformers 4.45.1
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- Pytorch 2.4.0
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- Datasets 3.0.1
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- Tokenizers 0.20.0
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