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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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- recall
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- f1
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model-index:
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- name: indic-bert-finetuned-code-mixed-DS
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# indic-bert-finetuned-code-mixed-DS
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This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8981
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- Accuracy: 0.5594
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- Precision: 0.3838
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- Recall: 0.5263
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- F1: 0.4118
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-06
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 43
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 1.0941 | 2.0 | 497 | 1.0845 | 0.3441 | 0.3615 | 0.4180 | 0.2706 |
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| 1.0379 | 3.99 | 994 | 0.9775 | 0.5412 | 0.3779 | 0.5128 | 0.4003 |
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| 0.9509 | 5.99 | 1491 | 0.9271 | 0.5513 | 0.3752 | 0.5144 | 0.4043 |
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| 0.9152 | 7.98 | 1988 | 0.9047 | 0.5614 | 0.3852 | 0.5275 | 0.4131 |
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| 0.8953 | 9.98 | 2485 | 0.8981 | 0.5594 | 0.3838 | 0.5263 | 0.4118 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.10.1+cu111
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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