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drug-combo-classifier-pubmedbert-dapt

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bert
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4

Add lightning checkpoint file to Drug Combo Extraction model

#3
by viswavi - opened
base: refs/heads/main
←
from: refs/pr/3
Discussion Files changed
+6
-31126
Files changed (11) hide show
  1. README.md +6 -16
  2. model.chkpt +0 -3
  3. outputs/eval_exact.txt +0 -1
  4. outputs/eval_partial.txt +0 -2
  5. outputs/predictions.jsonl +0 -289
  6. outputs/predictions.jsonl.bkp +0 -289
  7. tokenizer/added_tokens.json +0 -1
  8. tokenizer/special_tokens_map.json +0 -1
  9. tokenizer/tokenizer.json +0 -0
  10. tokenizer/tokenizer_config.json +0 -1
  11. tokenizer/vocab.txt +0 -0
README.md CHANGED
@@ -2,31 +2,21 @@
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  language: en
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  license: mit
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  ---
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- This is the baseline model used in most experiments in the paper ["A Dataset for N-ary Relation Extraction of Drug Combinations"](https://arxiv.org/abs/2205.02289).
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- *(for just the domain-adapted masked language model that we use underneath this model, see [here](https://huggingface.co/allenai/drug_combinations_lm_pubmedbert?text=Paxlovid+works+well+in+combination+with+%5BMASK%5D+for+treating+breast+cancer.))*
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-
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- **Steps to load this model**
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-
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- 1) Download accompanying code:
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- ```
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  git clone https://github.com/allenai/drug-combo-extraction.git
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  conda create --name drug_combo python=3.8.5
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  conda activate drug_combo
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- ```
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- 2) Download model from Huggingface:
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-
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- ```
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- git lfs install
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- git clone https://huggingface.co/allenai/drug-combo-classifier-pubmedbert-dapt
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- ```
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- 3) Load model (`in Python`):
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  ```
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  from modeling.model import load_model
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- checkpoint_path = "drug-combo-classifier-pubmedbert-dapt"
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  model, tokenizer, metadata = load_model(checkpoint_path)
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  ```
 
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  language: en
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  license: mit
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  ---
 
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+ How to load model:
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  git clone https://github.com/allenai/drug-combo-extraction.git
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  conda create --name drug_combo python=3.8.5
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  conda activate drug_combo
 
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+ cd drug-combo-extraction
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+ # download checkpoints_pubmedbert_cpt_2021_three_class.tgz
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+ tar -xvzf checkpoints_pubmedbert_cpt_2021_three_class.tgz
 
 
 
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+ python
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  ```
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  from modeling.model import load_model
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+ checkpoint_path = "checkpoints_pubmedbert_cpt_2021_three_class"
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  model, tokenizer, metadata = load_model(checkpoint_path)
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  ```
model.chkpt DELETED
@@ -1,3 +0,0 @@
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- version https://git-lfs.github.com/spec/v1
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- oid sha256:9d648b66745797958ab1395d9c719e5aa9201036030d09ba5c781e63fcb8310b
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- size 682321941
 
 
 
 
outputs/eval_exact.txt DELETED
@@ -1 +0,0 @@
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- F1/P/R score: unlabeled = (0.6917293233082706, 0.7263157894736842, 0.6602870813397129), labeled = (0.6233766233766234, 0.6075949367088608, 0.64)
 
 
outputs/eval_partial.txt DELETED
@@ -1,2 +0,0 @@
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- F1/P/R score: partial unlabeled = (0.7742675743982453, 0.8045614035087719, 0.7461722488038278), partial labeled = (0.6969071333846597, 0.6721518987341775, 0.7235555555555557)
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- F1/P/R score: exact unlabeled = (0.6917293233082706, 0.7263157894736842, 0.6602870813397129), exact labeled = (0.6233766233766234, 0.6075949367088608, 0.64)
 
 
 
outputs/predictions.jsonl DELETED
@@ -1,289 +0,0 @@
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