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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: IndicBERTv2-MLM-only-indic_glue |
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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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# IndicBERTv2-MLM-only-indic_glue |
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This model is a fine-tuned version of [ai4bharat/IndicBERTv2-MLM-only](https://huggingface.co/ai4bharat/IndicBERTv2-MLM-only) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1941 |
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- Precision: 0.8410 |
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- Recall: 0.8738 |
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- F1: 0.8571 |
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- Accuracy: 0.9427 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 64 |
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- seed: 42 |
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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: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.5734 | 0.31 | 200 | 0.2794 | 0.7618 | 0.7979 | 0.7794 | 0.9103 | |
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| 0.2767 | 0.62 | 400 | 0.2182 | 0.8139 | 0.8361 | 0.8248 | 0.9300 | |
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| 0.218 | 0.94 | 600 | 0.2058 | 0.8167 | 0.8648 | 0.8401 | 0.9365 | |
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| 0.1758 | 1.25 | 800 | 0.1995 | 0.8311 | 0.8641 | 0.8473 | 0.9380 | |
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| 0.1366 | 1.56 | 1000 | 0.1928 | 0.8430 | 0.8695 | 0.8561 | 0.9417 | |
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| 0.1349 | 1.88 | 1200 | 0.1941 | 0.8410 | 0.8738 | 0.8571 | 0.9427 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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