hipom_data_mapping/train
Richard Wong 086b867d91 Feat: added overall section to evaluate combined accuracy
- added relevant-class section
2024-12-24 21:57:48 +09:00
..
classification_bert_complete_desc Feat: added overall section to evaluate combined accuracy 2024-12-24 21:57:48 +09:00
classification_bert_complete_desc_unit Feat: added overall section to evaluate combined accuracy 2024-12-24 21:57:48 +09:00
classification_bert_complete_desc_unit_name Feat: added de_duplication post-processing method 2024-11-28 11:02:22 +09:00
classification_bert_pattern_desc Feat: added more classification and mapping variations 2024-11-25 18:15:28 +09:00
classification_bert_pattern_desc_unit Chore: re-organized train folders to have standardized naming schemes 2024-11-20 15:07:47 +09:00
classification_t5_complete Chore: re-organized train folders to have standardized naming schemes 2024-11-20 15:07:47 +09:00
classification_t5_complete_with_constrastive Chore: re-organized train folders to have standardized naming schemes 2024-11-20 15:07:47 +09:00
classification_t5_mdm_with_contrastive Chore: re-organized train folders to have standardized naming schemes 2024-11-20 15:07:47 +09:00
frozen_t5_decoder Feat: added modified layer-size decoder variants 2024-12-23 07:36:06 +09:00
frozen_t5_encoder Feat: added overall section to evaluate combined accuracy 2024-12-24 21:57:48 +09:00
hybrid_t5_complete_desc_unit Feat: added overall section to evaluate combined accuracy 2024-12-24 21:57:48 +09:00
hybrid_t5_pattern_desc_unit Feat: added overall section to evaluate combined accuracy 2024-12-24 21:57:48 +09:00
mapping_baseline Feat: implement find-back for analysis in find_closest.py 2024-11-08 20:50:41 +09:00
mapping_t5_complete_desc Feat: added more classification and mapping variations 2024-11-25 18:15:28 +09:00
mapping_t5_complete_desc_unit Feat: added overall section to evaluate combined accuracy 2024-12-24 21:57:48 +09:00
mapping_t5_complete_desc_unit_name Feat: added more classification and mapping variations 2024-11-25 18:15:28 +09:00
mapping_t5_final_delivery_model Feat: added post_processing based on rules 2024-12-18 13:43:56 +09:00
mapping_t5_pattern_desc_unit Chore: re-organized train folders to have standardized naming schemes 2024-11-20 15:07:47 +09:00
modified_t5_decoder_1_layers Feat: added modified layer-size decoder variants 2024-12-23 07:36:06 +09:00
modified_t5_decoder_2_layers Feat: added modified layer-size decoder variants 2024-12-23 07:36:06 +09:00
modified_t5_decoder_3_layers Feat: added modified layer-size decoder variants 2024-12-23 07:36:06 +09:00
modified_t5_decoder_4_layers Feat: added overall section to evaluate combined accuracy 2024-12-24 21:57:48 +09:00
modified_t5_decoder_8_layers Feat: added modified layer-size decoder variants 2024-12-23 07:36:06 +09:00
modified_t5_decoder_9_layers Feat: added modified layer-size decoder variants 2024-12-23 07:36:06 +09:00
modified_t5_decoder_12_layers Feat: added modified layer-size decoder variants 2024-12-23 07:36:06 +09:00
random_t5_encoder Feat: added overall section to evaluate combined accuracy 2024-12-24 21:57:48 +09:00
README.md Chore: re-organized train folders to have standardized naming schemes 2024-11-20 15:07:47 +09:00
predict.bash Feat: added more classification and mapping variations 2024-11-25 18:15:28 +09:00
train.bash Feat: added overall section to evaluate combined accuracy 2024-12-24 21:57:48 +09:00

README.md

Train

What is this folder

Here contains the code for training and mapping evaluation.

Each folder contains a training variation.

After training, each folder contains the checkpoint files for each fold.

The folders are named with the following convention:

<method_type>_<model_type>_<prediction_type>_<included_fields>

e.g.

"classification_bert_complete_desc_unit",

which means: folder to perform classification using the bert model, predicting for the complete thing+property output using description and unit

To train, just run python train.py

The inference code is within a folder classification_prediction or mapping_prediction.

Note: the classification_t5 folders are depracated in favor of the BERT-based classification models.