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Updated model card

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  1. README.md +0 -2
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@@ -19,8 +19,6 @@ It is trained on the following three financial communication corpus. The total c
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  - Corporate Reports 10-K & 10-Q: 2.5B tokens
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  - Earnings Call Transcripts: 1.3B tokens
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  - Analyst Reports: 1.1B tokens
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- - Demo.org Proprietary Reports
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- - Additional purchased data from Factset
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  The entire training is done using an **NVIDIA DGX-1** machine. The server has 4 Tesla P100 GPUs, providing a total of 128 GB of GPU memory. This machine enables us to train the BERT models using a batch size of 128. We utilize Horovord framework for multi-GPU training. Overall, the total time taken to perform pretraining for one model is approximately **2 days**.
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  - Corporate Reports 10-K & 10-Q: 2.5B tokens
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  - Earnings Call Transcripts: 1.3B tokens
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  - Analyst Reports: 1.1B tokens
 
 
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  The entire training is done using an **NVIDIA DGX-1** machine. The server has 4 Tesla P100 GPUs, providing a total of 128 GB of GPU memory. This machine enables us to train the BERT models using a batch size of 128. We utilize Horovord framework for multi-GPU training. Overall, the total time taken to perform pretraining for one model is approximately **2 days**.
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