Adding model, graphs and metadata.

README.md

@@ -28,7 +28,7 @@ The model contains **32.0%** of the original weights **overall** (the embeddings
 With a simple resizing of the linear matrices it ran **2.15x as fast as bert-large-uncased-whole-word-masking** on the evaluation.
 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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 In terms of accuracy, its **F1 is 83.22**, compared with 85.85 for , a **F1 drop of 2.63**.
 
@@ -38,7 +38,7 @@ This model is case-insensitive: it does not make a difference between english an
 
 A side-effect of the block pruning is that some of the attention heads are completely removed: 155 heads were removed on a total of 384 (40.4%).
 Here is a detailed view on how the remaining heads are distributed in the network after pruning.
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 ## Details of the SQuAD1.1 dataset
 

eval/eval_metrics.json

@@ -0,0 +1,15 @@
+{
+    "HasAns_exact": 76.48448043184885,
+    "HasAns_f1": 82.55514100819374,
+    "HasAns_total": 5928,
+    "NoAns_exact": 83.86879730866274,
+    "NoAns_f1": 83.86879730866274,
+    "NoAns_total": 5945,
+    "best_exact": 80.18192537690558,
+    "best_exact_thresh": 0.0,
+    "best_f1": 83.21290961817331,
+    "best_f1_thresh": 0.0,
+    "exact": 80.18192537690558,
+    "f1": 83.21290961817341,
+    "total": 11873
+}

eval/evaluate_timing.json

@@ -0,0 +1 @@
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eval/sparsity_report.json

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eval/speed_report.json

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model_card/density_info.js

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training/data_args.json

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+{
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+    "doc_stride": 128,
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+    "max_seq_length": 384,
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+    "overwrite_cache": 0,
+    "pad_to_max_length": true,
+    "preprocessing_num_workers": null,
+    "train_file": null,
+    "validation_file": null,
+    "version_2_with_negative": 1
+}

training/model_args.json

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+    "config_name": null,
+    "model_name_or_path": "bert-large-uncased-whole-word-masking",
+    "tokenizer_name": null,
+    "use_fast_tokenizer": true
+}

training/sparse_args.json

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+    "bias_mask": true,
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+    "dense_lambda": 1.0,
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+    "distil_temperature": 2.0,
+    "eval_with_current_patch_params": false,
+    "final_ampere_temperature": 20.0,
+    "final_finetune": false,
+    "final_threshold": 0.1,
+    "final_warmup": 10,
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