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---
license: cc-by-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: l3cube-pune/hing-mbert
model-index:
- name: hing-mbert-ours-run-2
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. -->
# hing-mbert-ours-run-2
This model is a fine-tuned version of [l3cube-pune/hing-mbert](https://huggingface.co/l3cube-pune/hing-mbert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3919
- Accuracy: 0.62
- Precision: 0.5759
- Recall: 0.5631
- F1: 0.5669
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.0284 | 1.0 | 100 | 1.2914 | 0.595 | 0.5712 | 0.4800 | 0.4642 |
| 0.8127 | 2.0 | 200 | 0.8552 | 0.59 | 0.5744 | 0.5675 | 0.4891 |
| 0.5499 | 3.0 | 300 | 1.1212 | 0.645 | 0.6544 | 0.5600 | 0.5475 |
| 0.3433 | 4.0 | 400 | 1.2017 | 0.605 | 0.5872 | 0.5866 | 0.5791 |
| 0.2218 | 5.0 | 500 | 1.8329 | 0.655 | 0.6458 | 0.6064 | 0.6055 |
| 0.1763 | 6.0 | 600 | 2.4194 | 0.655 | 0.6140 | 0.5802 | 0.5871 |
| 0.1022 | 7.0 | 700 | 2.3894 | 0.66 | 0.6171 | 0.6045 | 0.6048 |
| 0.0631 | 8.0 | 800 | 2.8259 | 0.605 | 0.5704 | 0.5255 | 0.5259 |
| 0.0254 | 9.0 | 900 | 2.9135 | 0.65 | 0.6013 | 0.5734 | 0.5784 |
| 0.0316 | 10.0 | 1000 | 3.0548 | 0.62 | 0.5862 | 0.5650 | 0.5670 |
| 0.026 | 11.0 | 1100 | 3.1020 | 0.62 | 0.5722 | 0.5593 | 0.5619 |
| 0.0152 | 12.0 | 1200 | 3.0692 | 0.62 | 0.5685 | 0.5597 | 0.5621 |
| 0.0156 | 13.0 | 1300 | 3.1068 | 0.615 | 0.5771 | 0.5589 | 0.5624 |
| 0.0237 | 14.0 | 1400 | 3.3487 | 0.62 | 0.5924 | 0.5589 | 0.5642 |
| 0.0094 | 15.0 | 1500 | 3.2007 | 0.615 | 0.5665 | 0.5639 | 0.5650 |
| 0.0054 | 16.0 | 1600 | 3.2838 | 0.62 | 0.5807 | 0.5657 | 0.5690 |
| 0.005 | 17.0 | 1700 | 3.2258 | 0.615 | 0.5846 | 0.5723 | 0.5747 |
| 0.005 | 18.0 | 1800 | 3.3572 | 0.63 | 0.5827 | 0.5698 | 0.5736 |
| 0.0022 | 19.0 | 1900 | 3.3642 | 0.62 | 0.5759 | 0.5631 | 0.5669 |
| 0.0019 | 20.0 | 2000 | 3.3919 | 0.62 | 0.5759 | 0.5631 | 0.5669 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Tokenizers 0.13.2
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