Chua, Vui Seng commited on
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1 Parent(s): b54a25c

Update readme, add collaterals and model analysis report

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.gitattributes CHANGED
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zstandard filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zstandard filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ optimizer.pt filter=lfs diff=lfs merge=lfs -text
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+ nbest_predictions.json filter=lfs diff=lfs merge=lfs -text
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+ eval_nbest_predictions.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ This model is a downstream fine-tuning of [```vuiseng9/bert-base-squadv1-block-pruning-hybrid```](https://huggingface.co/vuiseng9/bert-base-squadv1-block-pruning-hybrid). "filled" means unstructured fine-grained sparsified parameters are allowed to learn during fine-tuning. "lt" means distillation of larger model as teacher, i.e. ```bert-large-uncased-whole-word-masking-finetuned-squad```
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+
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+ ```
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+ eval_exact_match = 80.3311
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+ eval_f1 = 87.69
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+ eval_samples = 10784
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+ ```
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+ This model is a replication of [block pruning paper](https://arxiv.org/abs/2109.04838) with its open-sourced codebase (forked and modified).
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+ To reproduce this model, pls follow [documentation here](https://github.com/vuiseng9/nn_pruning/blob/reproduce-evaluation/reproduce-eval/readme.md) until step 3.
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+
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+ # Eval
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+ The model cannot be evaluated with HF QA example out-of-the-box as the final dimension of the model architecture has been realized. Follow the custom setup below.
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+
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+ ```bash
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+ # OpenVINO/NNCF
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+ git clone https://github.com/vuiseng9/nncf && cd nncf
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+ git checkout tld-poc
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+ git reset --hard 1dec7afe7a4b567c059fcf287ea2c234980fded2
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+ python setup.py develop
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+ pip install -r examples/torch/requirements.txt
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+
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+ # Huggingface nn_pruning
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+ git clone https://github.com/vuiseng9/nn_pruning && cd nn_pruning
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+ git checkout reproduce-evaluation
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+ git reset --hard 2d4e196d694c465e43e5fbce6c3836d0a60e1446
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+ pip install -e ".[dev]"
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+
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+ # Huggingface Transformers
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+ git clone https://github.com/vuiseng9/transformers && cd transformers
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+ git checkout tld-poc
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+ git reset --hard 10a1e29d84484e48fd106f58957d9ffc89dc43c5
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+ pip install -e .
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+ head -n 1 examples/pytorch/question-answering/requirements.txt | xargs -i pip install {}
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+
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+ ```
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+ This repo must be cloned locally.
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+ ```bash
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+ git clone https://huggingface.co/vuiseng9/bert-base-squadv1-block-pruning-hybrid-filled-lt
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+ ```
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+ Add ```--optimize_model_before_eval``` and ```--optimized_checkpoint /path/to/clone``` during evaluation.
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+
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+ ```bash
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+ export CUDA_VISIBLE_DEVICES=0
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+
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+ OUTDIR=eval-bert-base-squadv1-block-pruning-hybrid-filled-lt-cropped
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+ WORKDIR=transformers/examples/pytorch/question-answering
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+ cd $WORKDIR
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+ mkdir $OUTDIR
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+
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+ nohup python run_qa.py \
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+ --model_name_or_path vuiseng9/bert-base-squadv1-block-pruning-hybrid \
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+ --dataset_name squad \
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+ --optimize_model_before_eval \
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+ --optimized_checkpoint /path/to/clone/bert-base-squadv1-block-pruning-hybrid-filled-lt \
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+ --do_eval \
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+ --per_device_eval_batch_size 16 \
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+ --max_seq_length 384 \
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+ --doc_stride 128 \
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+ --overwrite_output_dir \
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+ --output_dir $OUTDIR 2>&1 | tee $OUTDIR/run.log &
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+ ```
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XP_layer_wise_sparsity_global_rate_0.00.md ADDED
@@ -0,0 +1,201 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ | | layer_id | layer_type | param_type | shape | nparam | nnz | sparsity |
2
+ |----:|:-------------------------------------------------|:-------------|:-------------|:-------------|---------:|---------:|------------:|
3
+ | 0 | bert.embeddings.word_embeddings | Embedding | weight | [30522, 768] | 23440896 | 23440896 | 0 |
4
+ | 1 | bert.embeddings.position_embeddings | Embedding | weight | [512, 768] | 393216 | 393216 | 0 |
5
+ | 2 | bert.embeddings.token_type_embeddings | Embedding | weight | [2, 768] | 1536 | 1536 | 0 |
6
+ | 3 | bert.embeddings.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
7
+ | 4 | bert.embeddings.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
8
+ | 5 | bert.encoder.layer.0.attention.self.query | Linear | weight | [320, 768] | 245760 | 245760 | 0 |
9
+ | 6 | bert.encoder.layer.0.attention.self.query | Linear | bias | [320] | 320 | 320 | 0 |
10
+ | 7 | bert.encoder.layer.0.attention.self.key | Linear | weight | [320, 768] | 245760 | 245760 | 0 |
11
+ | 8 | bert.encoder.layer.0.attention.self.key | Linear | bias | [320] | 320 | 320 | 0 |
12
+ | 9 | bert.encoder.layer.0.attention.self.value | Linear | weight | [320, 768] | 245760 | 245760 | 0 |
13
+ | 10 | bert.encoder.layer.0.attention.self.value | Linear | bias | [320] | 320 | 320 | 0 |
14
+ | 11 | bert.encoder.layer.0.attention.output.dense | Linear | weight | [768, 320] | 245760 | 245760 | 0 |
15
+ | 12 | bert.encoder.layer.0.attention.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
16
+ | 13 | bert.encoder.layer.0.attention.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
17
+ | 14 | bert.encoder.layer.0.attention.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
18
+ | 15 | bert.encoder.layer.0.intermediate.dense | Linear | weight | [185, 768] | 142080 | 142080 | 0 |
19
+ | 16 | bert.encoder.layer.0.intermediate.dense | Linear | bias | [185] | 185 | 185 | 0 |
20
+ | 17 | bert.encoder.layer.0.output.dense | Linear | weight | [768, 185] | 142080 | 142080 | 0 |
21
+ | 18 | bert.encoder.layer.0.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
22
+ | 19 | bert.encoder.layer.0.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
23
+ | 20 | bert.encoder.layer.0.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
24
+ | 21 | bert.encoder.layer.1.attention.self.query | Linear | weight | [320, 768] | 245760 | 245760 | 0 |
25
+ | 22 | bert.encoder.layer.1.attention.self.query | Linear | bias | [320] | 320 | 320 | 0 |
26
+ | 23 | bert.encoder.layer.1.attention.self.key | Linear | weight | [320, 768] | 245760 | 245760 | 0 |
27
+ | 24 | bert.encoder.layer.1.attention.self.key | Linear | bias | [320] | 320 | 320 | 0 |
28
+ | 25 | bert.encoder.layer.1.attention.self.value | Linear | weight | [320, 768] | 245760 | 245760 | 0 |
29
+ | 26 | bert.encoder.layer.1.attention.self.value | Linear | bias | [320] | 320 | 320 | 0 |
30
+ | 27 | bert.encoder.layer.1.attention.output.dense | Linear | weight | [768, 320] | 245760 | 245760 | 0 |
31
+ | 28 | bert.encoder.layer.1.attention.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
32
+ | 29 | bert.encoder.layer.1.attention.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
33
+ | 30 | bert.encoder.layer.1.attention.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
34
+ | 31 | bert.encoder.layer.1.intermediate.dense | Linear | weight | [315, 768] | 241920 | 241920 | 0 |
35
+ | 32 | bert.encoder.layer.1.intermediate.dense | Linear | bias | [315] | 315 | 315 | 0 |
36
+ | 33 | bert.encoder.layer.1.output.dense | Linear | weight | [768, 315] | 241920 | 241920 | 0 |
37
+ | 34 | bert.encoder.layer.1.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
38
+ | 35 | bert.encoder.layer.1.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
39
+ | 36 | bert.encoder.layer.1.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
40
+ | 37 | bert.encoder.layer.2.attention.self.query | Linear | weight | [576, 768] | 442368 | 442368 | 0 |
41
+ | 38 | bert.encoder.layer.2.attention.self.query | Linear | bias | [576] | 576 | 576 | 0 |
42
+ | 39 | bert.encoder.layer.2.attention.self.key | Linear | weight | [576, 768] | 442368 | 442368 | 0 |
43
+ | 40 | bert.encoder.layer.2.attention.self.key | Linear | bias | [576] | 576 | 576 | 0 |
44
+ | 41 | bert.encoder.layer.2.attention.self.value | Linear | weight | [576, 768] | 442368 | 442368 | 0 |
45
+ | 42 | bert.encoder.layer.2.attention.self.value | Linear | bias | [576] | 576 | 576 | 0 |
46
+ | 43 | bert.encoder.layer.2.attention.output.dense | Linear | weight | [768, 576] | 442368 | 442368 | 0 |
47
+ | 44 | bert.encoder.layer.2.attention.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
48
+ | 45 | bert.encoder.layer.2.attention.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
49
+ | 46 | bert.encoder.layer.2.attention.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
50
+ | 47 | bert.encoder.layer.2.intermediate.dense | Linear | weight | [339, 768] | 260352 | 260352 | 0 |
51
+ | 48 | bert.encoder.layer.2.intermediate.dense | Linear | bias | [339] | 339 | 339 | 0 |
52
+ | 49 | bert.encoder.layer.2.output.dense | Linear | weight | [768, 339] | 260352 | 260352 | 0 |
53
+ | 50 | bert.encoder.layer.2.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
54
+ | 51 | bert.encoder.layer.2.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
55
+ | 52 | bert.encoder.layer.2.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
56
+ | 53 | bert.encoder.layer.3.attention.self.query | Linear | weight | [576, 768] | 442368 | 442368 | 0 |
57
+ | 54 | bert.encoder.layer.3.attention.self.query | Linear | bias | [576] | 576 | 576 | 0 |
58
+ | 55 | bert.encoder.layer.3.attention.self.key | Linear | weight | [576, 768] | 442368 | 442368 | 0 |
59
+ | 56 | bert.encoder.layer.3.attention.self.key | Linear | bias | [576] | 576 | 576 | 0 |
60
+ | 57 | bert.encoder.layer.3.attention.self.value | Linear | weight | [576, 768] | 442368 | 442368 | 0 |
61
+ | 58 | bert.encoder.layer.3.attention.self.value | Linear | bias | [576] | 576 | 576 | 0 |
62
+ | 59 | bert.encoder.layer.3.attention.output.dense | Linear | weight | [768, 576] | 442368 | 442368 | 0 |
63
+ | 60 | bert.encoder.layer.3.attention.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
64
+ | 61 | bert.encoder.layer.3.attention.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
65
+ | 62 | bert.encoder.layer.3.attention.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
66
+ | 63 | bert.encoder.layer.3.intermediate.dense | Linear | weight | [368, 768] | 282624 | 282624 | 0 |
67
+ | 64 | bert.encoder.layer.3.intermediate.dense | Linear | bias | [368] | 368 | 368 | 0 |
68
+ | 65 | bert.encoder.layer.3.output.dense | Linear | weight | [768, 368] | 282624 | 282624 | 0 |
69
+ | 66 | bert.encoder.layer.3.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
70
+ | 67 | bert.encoder.layer.3.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
71
+ | 68 | bert.encoder.layer.3.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
72
+ | 69 | bert.encoder.layer.4.attention.self.query | Linear | weight | [576, 768] | 442368 | 442368 | 0 |
73
+ | 70 | bert.encoder.layer.4.attention.self.query | Linear | bias | [576] | 576 | 576 | 0 |
74
+ | 71 | bert.encoder.layer.4.attention.self.key | Linear | weight | [576, 768] | 442368 | 442368 | 0 |
75
+ | 72 | bert.encoder.layer.4.attention.self.key | Linear | bias | [576] | 576 | 576 | 0 |
76
+ | 73 | bert.encoder.layer.4.attention.self.value | Linear | weight | [576, 768] | 442368 | 442368 | 0 |
77
+ | 74 | bert.encoder.layer.4.attention.self.value | Linear | bias | [576] | 576 | 576 | 0 |
78
+ | 75 | bert.encoder.layer.4.attention.output.dense | Linear | weight | [768, 576] | 442368 | 442368 | 0 |
79
+ | 76 | bert.encoder.layer.4.attention.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
80
+ | 77 | bert.encoder.layer.4.attention.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
81
+ | 78 | bert.encoder.layer.4.attention.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
82
+ | 79 | bert.encoder.layer.4.intermediate.dense | Linear | weight | [386, 768] | 296448 | 296448 | 0 |
83
+ | 80 | bert.encoder.layer.4.intermediate.dense | Linear | bias | [386] | 386 | 386 | 0 |
84
+ | 81 | bert.encoder.layer.4.output.dense | Linear | weight | [768, 386] | 296448 | 296448 | 0 |
85
+ | 82 | bert.encoder.layer.4.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
86
+ | 83 | bert.encoder.layer.4.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
87
+ | 84 | bert.encoder.layer.4.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
88
+ | 85 | bert.encoder.layer.5.attention.self.query | Linear | weight | [384, 768] | 294912 | 294912 | 0 |
89
+ | 86 | bert.encoder.layer.5.attention.self.query | Linear | bias | [384] | 384 | 384 | 0 |
90
+ | 87 | bert.encoder.layer.5.attention.self.key | Linear | weight | [384, 768] | 294912 | 294912 | 0 |
91
+ | 88 | bert.encoder.layer.5.attention.self.key | Linear | bias | [384] | 384 | 384 | 0 |
92
+ | 89 | bert.encoder.layer.5.attention.self.value | Linear | weight | [384, 768] | 294912 | 294912 | 0 |
93
+ | 90 | bert.encoder.layer.5.attention.self.value | Linear | bias | [384] | 384 | 384 | 0 |
94
+ | 91 | bert.encoder.layer.5.attention.output.dense | Linear | weight | [768, 384] | 294912 | 294912 | 0 |
95
+ | 92 | bert.encoder.layer.5.attention.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
96
+ | 93 | bert.encoder.layer.5.attention.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
97
+ | 94 | bert.encoder.layer.5.attention.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
98
+ | 95 | bert.encoder.layer.5.intermediate.dense | Linear | weight | [336, 768] | 258048 | 258048 | 0 |
99
+ | 96 | bert.encoder.layer.5.intermediate.dense | Linear | bias | [336] | 336 | 336 | 0 |
100
+ | 97 | bert.encoder.layer.5.output.dense | Linear | weight | [768, 336] | 258048 | 258048 | 0 |
101
+ | 98 | bert.encoder.layer.5.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
102
+ | 99 | bert.encoder.layer.5.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
103
+ | 100 | bert.encoder.layer.5.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
104
+ | 101 | bert.encoder.layer.6.attention.self.query | Linear | weight | [448, 768] | 344064 | 344064 | 0 |
105
+ | 102 | bert.encoder.layer.6.attention.self.query | Linear | bias | [448] | 448 | 448 | 0 |
106
+ | 103 | bert.encoder.layer.6.attention.self.key | Linear | weight | [448, 768] | 344064 | 344064 | 0 |
107
+ | 104 | bert.encoder.layer.6.attention.self.key | Linear | bias | [448] | 448 | 448 | 0 |
108
+ | 105 | bert.encoder.layer.6.attention.self.value | Linear | weight | [448, 768] | 344064 | 344064 | 0 |
109
+ | 106 | bert.encoder.layer.6.attention.self.value | Linear | bias | [448] | 448 | 448 | 0 |
110
+ | 107 | bert.encoder.layer.6.attention.output.dense | Linear | weight | [768, 448] | 344064 | 344064 | 0 |
111
+ | 108 | bert.encoder.layer.6.attention.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
112
+ | 109 | bert.encoder.layer.6.attention.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
113
+ | 110 | bert.encoder.layer.6.attention.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
114
+ | 111 | bert.encoder.layer.6.intermediate.dense | Linear | weight | [280, 768] | 215040 | 215040 | 0 |
115
+ | 112 | bert.encoder.layer.6.intermediate.dense | Linear | bias | [280] | 280 | 280 | 0 |
116
+ | 113 | bert.encoder.layer.6.output.dense | Linear | weight | [768, 280] | 215040 | 215040 | 0 |
117
+ | 114 | bert.encoder.layer.6.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
118
+ | 115 | bert.encoder.layer.6.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
119
+ | 116 | bert.encoder.layer.6.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
120
+ | 117 | bert.encoder.layer.7.attention.self.query | Linear | weight | [448, 768] | 344064 | 344064 | 0 |
121
+ | 118 | bert.encoder.layer.7.attention.self.query | Linear | bias | [448] | 448 | 448 | 0 |
122
+ | 119 | bert.encoder.layer.7.attention.self.key | Linear | weight | [448, 768] | 344064 | 344064 | 0 |
123
+ | 120 | bert.encoder.layer.7.attention.self.key | Linear | bias | [448] | 448 | 448 | 0 |
124
+ | 121 | bert.encoder.layer.7.attention.self.value | Linear | weight | [448, 768] | 344064 | 344064 | 0 |
125
+ | 122 | bert.encoder.layer.7.attention.self.value | Linear | bias | [448] | 448 | 448 | 0 |
126
+ | 123 | bert.encoder.layer.7.attention.output.dense | Linear | weight | [768, 448] | 344064 | 344064 | 0 |
127
+ | 124 | bert.encoder.layer.7.attention.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
128
+ | 125 | bert.encoder.layer.7.attention.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
129
+ | 126 | bert.encoder.layer.7.attention.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
130
+ | 127 | bert.encoder.layer.7.intermediate.dense | Linear | weight | [211, 768] | 162048 | 162048 | 0 |
131
+ | 128 | bert.encoder.layer.7.intermediate.dense | Linear | bias | [211] | 211 | 211 | 0 |
132
+ | 129 | bert.encoder.layer.7.output.dense | Linear | weight | [768, 211] | 162048 | 162048 | 0 |
133
+ | 130 | bert.encoder.layer.7.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
134
+ | 131 | bert.encoder.layer.7.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
135
+ | 132 | bert.encoder.layer.7.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
136
+ | 133 | bert.encoder.layer.8.attention.self.query | Linear | weight | [448, 768] | 344064 | 344064 | 0 |
137
+ | 134 | bert.encoder.layer.8.attention.self.query | Linear | bias | [448] | 448 | 448 | 0 |
138
+ | 135 | bert.encoder.layer.8.attention.self.key | Linear | weight | [448, 768] | 344064 | 344064 | 0 |
139
+ | 136 | bert.encoder.layer.8.attention.self.key | Linear | bias | [448] | 448 | 448 | 0 |
140
+ | 137 | bert.encoder.layer.8.attention.self.value | Linear | weight | [448, 768] | 344064 | 344064 | 0 |
141
+ | 138 | bert.encoder.layer.8.attention.self.value | Linear | bias | [448] | 448 | 448 | 0 |
142
+ | 139 | bert.encoder.layer.8.attention.output.dense | Linear | weight | [768, 448] | 344064 | 344064 | 0 |
143
+ | 140 | bert.encoder.layer.8.attention.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
144
+ | 141 | bert.encoder.layer.8.attention.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
145
+ | 142 | bert.encoder.layer.8.attention.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
146
+ | 143 | bert.encoder.layer.8.intermediate.dense | Linear | weight | [108, 768] | 82944 | 82944 | 0 |
147
+ | 144 | bert.encoder.layer.8.intermediate.dense | Linear | bias | [108] | 108 | 108 | 0 |
148
+ | 145 | bert.encoder.layer.8.output.dense | Linear | weight | [768, 108] | 82944 | 82944 | 0 |
149
+ | 146 | bert.encoder.layer.8.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
150
+ | 147 | bert.encoder.layer.8.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
151
+ | 148 | bert.encoder.layer.8.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
152
+ | 149 | bert.encoder.layer.9.attention.self.query | Linear | weight | [320, 768] | 245760 | 245760 | 0 |
153
+ | 150 | bert.encoder.layer.9.attention.self.query | Linear | bias | [320] | 320 | 320 | 0 |
154
+ | 151 | bert.encoder.layer.9.attention.self.key | Linear | weight | [320, 768] | 245760 | 245760 | 0 |
155
+ | 152 | bert.encoder.layer.9.attention.self.key | Linear | bias | [320] | 320 | 320 | 0 |
156
+ | 153 | bert.encoder.layer.9.attention.self.value | Linear | weight | [320, 768] | 245760 | 245760 | 0 |
157
+ | 154 | bert.encoder.layer.9.attention.self.value | Linear | bias | [320] | 320 | 320 | 0 |
158
+ | 155 | bert.encoder.layer.9.attention.output.dense | Linear | weight | [768, 320] | 245760 | 245760 | 0 |
159
+ | 156 | bert.encoder.layer.9.attention.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
160
+ | 157 | bert.encoder.layer.9.attention.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
161
+ | 158 | bert.encoder.layer.9.attention.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
162
+ | 159 | bert.encoder.layer.9.intermediate.dense | Linear | weight | [53, 768] | 40704 | 40704 | 5.96046e-08 |
163
+ | 160 | bert.encoder.layer.9.intermediate.dense | Linear | bias | [53] | 53 | 53 | 0 |
164
+ | 161 | bert.encoder.layer.9.output.dense | Linear | weight | [768, 53] | 40704 | 40704 | 5.96046e-08 |
165
+ | 162 | bert.encoder.layer.9.output.dense | Linear | bias | [768] | 768 | 768 | 0 |
166
+ | 163 | bert.encoder.layer.9.output.LayerNorm | LayerNorm | weight | [768] | 768 | 768 | 0 |
167
+ | 164 | bert.encoder.layer.9.output.LayerNorm | LayerNorm | bias | [768] | 768 | 768 | 0 |
168
+ | 165 | bert.encoder.layer.10.attention.self.query | Linear | weight | [384, 768] | 294912 | 294912 | 0 |
169
+ | 166 | bert.encoder.layer.10.attention.self.query | Linear | bias | [384] | 384 | 384 | 0 |
170
+ | 167 | bert.encoder.layer.10.attention.self.key | Linear | weight | [384, 768] | 294912 | 294912 | 0 |
171
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172
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173
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174
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175
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1
+ | | layer_id | layer_type | param_type | shape | nparam | nnz | sparsity |
2
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3
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4
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5
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6
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7
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8
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9
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10
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11
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12
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13
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14
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15
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16
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17
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18
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19
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20
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21
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22
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23
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24
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25
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26
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27
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28
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29
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30
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31
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32
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33
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34
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35
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36
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37
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38
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39
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40
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41
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42
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43
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44
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45
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46
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47
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48
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49
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50
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51
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52
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53
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54
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55
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56
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57
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58
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59
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60
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61
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62
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63
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64
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65
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66
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67
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68
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69
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70
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71
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72
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73
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74
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config.json ADDED
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2
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