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---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: IndicBERTv2-MLM-only-indic_glue
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. -->
# IndicBERTv2-MLM-only-indic_glue
This model is a fine-tuned version of [ai4bharat/IndicBERTv2-MLM-only](https://huggingface.co/ai4bharat/IndicBERTv2-MLM-only) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1941
- Precision: 0.8410
- Recall: 0.8738
- F1: 0.8571
- Accuracy: 0.9427
## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5734 | 0.31 | 200 | 0.2794 | 0.7618 | 0.7979 | 0.7794 | 0.9103 |
| 0.2767 | 0.62 | 400 | 0.2182 | 0.8139 | 0.8361 | 0.8248 | 0.9300 |
| 0.218 | 0.94 | 600 | 0.2058 | 0.8167 | 0.8648 | 0.8401 | 0.9365 |
| 0.1758 | 1.25 | 800 | 0.1995 | 0.8311 | 0.8641 | 0.8473 | 0.9380 |
| 0.1366 | 1.56 | 1000 | 0.1928 | 0.8430 | 0.8695 | 0.8561 | 0.9417 |
| 0.1349 | 1.88 | 1200 | 0.1941 | 0.8410 | 0.8738 | 0.8571 | 0.9427 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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