madlag commited on
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1 Parent(s): 74a9437

Adding model, graphs and metadata.

Browse files
README.md CHANGED
@@ -28,7 +28,7 @@ The model contains **24.0%** of the original weights **overall** (the embeddings
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  With a simple resizing of the linear matrices it ran **2.63x as fast as bert-large-uncased-whole-word-masking** on the evaluation.
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  This is possible because the pruning method lead to structured matrices: to visualize them, hover below on the plot to see the non-zero/zero parts of each matrix.
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- <div class="graph"><script src="/madlag/bert-large-uncased-wwm-squadv2-x2.63-f82.6-d16-hybrid-v1/raw/main/model_card/density_info.js" id="64b46a6e-dbe2-4f43-83f9-470cbe9b6ced"></script></div>
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  In terms of accuracy, its **F1 is 82.57**, compared with 85.85 for , a **F1 drop of 3.28**.
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@@ -38,7 +38,7 @@ This model is case-insensitive: it does not make a difference between english an
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  A side-effect of the block pruning is that some of the attention heads are completely removed: 190 heads were removed on a total of 384 (49.5%).
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  Here is a detailed view on how the remaining heads are distributed in the network after pruning.
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- <div class="graph"><script src="/madlag/bert-large-uncased-wwm-squadv2-x2.63-f82.6-d16-hybrid-v1/raw/main/model_card/pruning_info.js" id="c81effce-5f17-4643-b14a-e5e982bed699"></script></div>
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  ## Details of the SQuAD1.1 dataset
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  With a simple resizing of the linear matrices it ran **2.63x as fast as bert-large-uncased-whole-word-masking** on the evaluation.
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  This is possible because the pruning method lead to structured matrices: to visualize them, hover below on the plot to see the non-zero/zero parts of each matrix.
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+ <div class="graph"><script src="/madlag/bert-large-uncased-wwm-squadv2-x2.63-f82.6-d16-hybrid-v1/raw/main/model_card/density_info.js" id="0ec8d8c8-9ab6-44ee-b565-45de8ecc6862"></script></div>
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  In terms of accuracy, its **F1 is 82.57**, compared with 85.85 for , a **F1 drop of 3.28**.
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  A side-effect of the block pruning is that some of the attention heads are completely removed: 190 heads were removed on a total of 384 (49.5%).
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  Here is a detailed view on how the remaining heads are distributed in the network after pruning.
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+ <div class="graph"><script src="/madlag/bert-large-uncased-wwm-squadv2-x2.63-f82.6-d16-hybrid-v1/raw/main/model_card/pruning_info.js" id="3a4845eb-b430-422c-b4bb-b1f5586a91af"></script></div>
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  ## Details of the SQuAD1.1 dataset
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eval/nbest_predictions.json.tgz CHANGED
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model_card/density_info.js CHANGED
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119
- var render_items = [{"docid":"db9c60ce-feb7-4e96-b7a0-bd8663fdcd25","root_ids":["1095"],"roots":{"1095":"64b46a6e-dbe2-4f43-83f9-470cbe9b6ced"}}];
120
  root.Bokeh.embed.embed_items(docs_json, render_items);
121
 
122
  }
 
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+ var element = document.getElementById("0ec8d8c8-9ab6-44ee-b565-45de8ecc6862");
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