Update prot-t5-xl from elnaggar

README.md

@@ -3,10 +3,10 @@ language: protein
 tags:
 - protein language model
 datasets:
-- BFD
+- UniRef50
 ---
 
-# ProtT5-XL-BFD model
+# ProtT5-XL-UniRef50 model
 
 Pretrained model on protein sequences using a masked language modeling (MLM) objective. It was introduced in
 [this paper](https://doi.org/10.1101/2020.07.12.199554) and first released in
@@ -87,7 +87,7 @@ The details of the masking procedure for each sequence are as follows:
 
 ### Pretraining
 
-The model was trained on a single TPU Pod V2-256 for 600 thousand steps in total, using sequence length 512 (batch size 2k).
+The model was trained on a single TPU Pod V2-256 for 991.5 thousand steps in total, using sequence length 512 (batch size 2k).
 It was trained using ProtT5-XL-BFD model as an initial checkpoint, rather than training from scratch.  
 It has a total of approximately 3B parameters and was trained using the encoder-decoder architecture.
 The optimizer used is AdaFactor with inverse square root learning rate schedule for pre-training.

pytorch_model.bin

@@ -1,3 +1,3 @@
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+size 11275562724

pytorch_model_723k.bin

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