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run_inference_for_ner.sh
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run_inference_for_ner.sh
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#!/bin/bash
# CARTONNER trained on CSQA dataset for 10 epochs
python inference_for_ner_recall.py --name "00_csqa10_on_csqa" --batch-size 25 --model-path experiments/models/CARTONNER_csqa15_e10_v0.0145_multitask.pth.tar --data-path data/final/csqa --cuda-device 1
python inference_for_ner_recall.py --name "00_csqa10_on_merged" --batch-size 25 --model-path experiments/models/CARTONNER_csqa15_e10_v0.0145_multitask.pth.tar --data-path data/csqa-merged --cuda-device 1
python inference_for_ner_recall.py --name "00_csqa10_on_d2t" --batch-size 25 --model-path experiments/models/CARTONNER_csqa15_e10_v0.0145_multitask.pth.tar --data-path data/d2t-sampled --cuda-device 1
# CARTONNER trained on MERGED dataset for 10 epochs
python inference_for_ner_recall.py --name "01_merged10_on_csqa" --batch-size 25 --model-path experiments/models/CARTONNER_merged15_e10_v0.0258_multitask.pth.tar --data-path data/final/csqa --cuda-device 1
python inference_for_ner_recall.py --name "01_merged10_on_merged" --batch-size 25 --model-path experiments/models/CARTONNER_merged15_e10_v0.0258_multitask.pth.tar --data-path data/csqa-merged --cuda-device 1
python inference_for_ner_recall.py --name "01_merged10_on_d2t" --batch-size 25 --model-path experiments/models/CARTONNER_merged15_e10_v0.0258_multitask.pth.tar --data-path data/d2t-sampled --cuda-device 1
# CARTONNER trained on CSQA dataset for 15 epochs
python inference_for_ner_recall.py --name "02_csqa15_on_csqa" --batch-size 25 --model-path experiments/models/CARTONNER_csqa15_e15_v0.0141_multitask.pth.tar --data-path data/final/csqa --cuda-device 1
python inference_for_ner_recall.py --name "02_csqa15_on_merged" --batch-size 25 --model-path experiments/models/CARTONNER_csqa15_e15_v0.0141_multitask.pth.tar --data-path data/csqa-merged --cuda-device 1
python inference_for_ner_recall.py --name "02_csqa15_on_d2t" --batch-size 25 --model-path experiments/models/CARTONNER_csqa15_e15_v0.0141_multitask.pth.tar --data-path data/d2t-sampled --cuda-device 1
# CARTONNER trained on MERGED dataset for 15 epochs
python inference_for_ner_recall.py --name "03_merged15_on_csqa" --batch-size 25 --model-path experiments/models/CARTONNER_merged15_e15_v0.0258_multitask.pth.tar --data-path data/final/csqa --cuda-device 1
python inference_for_ner_recall.py --name "03_merged15_on_merged" --batch-size 25 --model-path experiments/models/CARTONNER_merged15_e15_v0.0258_multitask.pth.tar --data-path data/csqa-merged --cuda-device 1
python inference_for_ner_recall.py --name "03_merged15_on_d2t" --batch-size 25 --model-path experiments/models/CARTONNER_merged15_e15_v0.0258_multitask.pth.tar --data-path data/d2t-sampled --cuda-device 1