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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-4
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-4
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: 3.0173
- Accuracy: 0.68
- Precision: 0.6330
- Recall: 0.6325
- F1: 0.6320
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.9781 | 1.0 | 100 | 0.8852 | 0.55 | 0.4044 | 0.5284 | 0.4211 |
| 0.7568 | 2.0 | 200 | 0.8110 | 0.655 | 0.5994 | 0.6013 | 0.5762 |
| 0.5121 | 3.0 | 300 | 0.9735 | 0.65 | 0.6145 | 0.6131 | 0.5965 |
| 0.314 | 4.0 | 400 | 1.1324 | 0.65 | 0.6305 | 0.6355 | 0.6266 |
| 0.1298 | 5.0 | 500 | 2.8247 | 0.61 | 0.5804 | 0.5087 | 0.5092 |
| 0.1013 | 6.0 | 600 | 2.8183 | 0.635 | 0.6212 | 0.5674 | 0.5667 |
| 0.0989 | 7.0 | 700 | 2.3235 | 0.635 | 0.5944 | 0.5922 | 0.5916 |
| 0.0481 | 8.0 | 800 | 2.5240 | 0.68 | 0.6334 | 0.6172 | 0.6221 |
| 0.018 | 9.0 | 900 | 2.6782 | 0.65 | 0.6123 | 0.6054 | 0.6062 |
| 0.0285 | 10.0 | 1000 | 2.3400 | 0.67 | 0.6206 | 0.6327 | 0.6189 |
| 0.014 | 11.0 | 1100 | 2.6558 | 0.66 | 0.6098 | 0.5992 | 0.6018 |
| 0.0085 | 12.0 | 1200 | 2.9366 | 0.66 | 0.6076 | 0.5961 | 0.5991 |
| 0.0106 | 13.0 | 1300 | 2.8567 | 0.665 | 0.6198 | 0.6193 | 0.6186 |
| 0.0097 | 14.0 | 1400 | 3.1526 | 0.64 | 0.6089 | 0.5975 | 0.5954 |
| 0.0022 | 15.0 | 1500 | 2.7305 | 0.69 | 0.6404 | 0.6404 | 0.6398 |
| 0.0016 | 16.0 | 1600 | 2.7670 | 0.69 | 0.6418 | 0.6434 | 0.6425 |
| 0.0017 | 17.0 | 1700 | 2.8193 | 0.7 | 0.6533 | 0.6566 | 0.6546 |
| 0.0009 | 18.0 | 1800 | 2.9959 | 0.685 | 0.6400 | 0.6389 | 0.6384 |
| 0.0006 | 19.0 | 1900 | 3.0153 | 0.68 | 0.6330 | 0.6325 | 0.6320 |
| 0.0005 | 20.0 | 2000 | 3.0173 | 0.68 | 0.6330 | 0.6325 | 0.6320 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Tokenizers 0.13.2
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