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---
library_name: transformers
license: cc-by-4.0
base_model: l3cube-pune/indic-sentence-bert-nli
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: indic-sentence-bert-nli-hinglish-binary
results: []
---
<!-- 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](https://huggingface.co/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
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