add animations to model card
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README.md
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# sahajBERT
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Collaboratively pre-trained model on Bengali language using masked language modeling (MLM) and Sentence Order Prediction (SOP) objectives.
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## Model description
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|39|[Rounak](https://huggingface.co/Rounak)|0 days 00:26:10|
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|40|[kshmax](https://huggingface.co/kshmax)|0 days 00:06:38|
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## Eval results
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We evaluate sahajBERT model quality and 2 other model benchmarks ([XLM-R-large](https://huggingface.co/xlm-roberta-large) and [IndicBert](https://huggingface.co/ai4bharat/indic-bert)) by fine-tuning 3 times their pre-trained models on two downstream tasks in Bengali:
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# sahajBERT
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<iframe width="100%" height="1100" frameborder="0"
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src="https://observablehq.com/embed/@huggingface/participants-bubbles-chart?cells=c_noaws%2Ct_noaws%2Cviewof+currentDate"></iframe>
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Collaboratively pre-trained model on Bengali language using masked language modeling (MLM) and Sentence Order Prediction (SOP) objectives.
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## Model description
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|39|[Rounak](https://huggingface.co/Rounak)|0 days 00:26:10|
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|40|[kshmax](https://huggingface.co/kshmax)|0 days 00:06:38|
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### Hardware used
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<iframe width="100%" height="251" frameborder="0"
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src="https://observablehq.com/embed/@huggingface/sahajbert-hardware?cells=c1_noaws"></iframe>
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## Eval results
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We evaluate sahajBERT model quality and 2 other model benchmarks ([XLM-R-large](https://huggingface.co/xlm-roberta-large) and [IndicBert](https://huggingface.co/ai4bharat/indic-bert)) by fine-tuning 3 times their pre-trained models on two downstream tasks in Bengali:
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