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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: indic-bert-finetuned-code-mixed-DS
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-bert-finetuned-code-mixed-DS
This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co./ai4bharat/indic-bert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8981
- Accuracy: 0.5594
- Precision: 0.3838
- Recall: 0.5263
- F1: 0.4118
## 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: 1e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 43
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.0941 | 2.0 | 497 | 1.0845 | 0.3441 | 0.3615 | 0.4180 | 0.2706 |
| 1.0379 | 3.99 | 994 | 0.9775 | 0.5412 | 0.3779 | 0.5128 | 0.4003 |
| 0.9509 | 5.99 | 1491 | 0.9271 | 0.5513 | 0.3752 | 0.5144 | 0.4043 |
| 0.9152 | 7.98 | 1988 | 0.9047 | 0.5614 | 0.3852 | 0.5275 | 0.4131 |
| 0.8953 | 9.98 | 2485 | 0.8981 | 0.5594 | 0.3838 | 0.5263 | 0.4118 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1
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