| { | |
| "model_save_dir": "models", | |
| "model_save_name": "linkage_un_data_fr_fine_industry", | |
| "opt_model_description": "This model was trained on a dataset prepared by linking product classifications from [UN stats](https://unstats.un.org/unsd/classifications/Econ). \n This model is designed to link different products to their industrial classification (ISIC) - trained on variation brought on by product level correspondance. It was trained for 70 epochs using other defaults that can be found in the repo's LinkTransformer config file - LT_training_config.json \n ", | |
| "opt_model_lang": "fr", | |
| "train_batch_size": 64, | |
| "num_epochs": 70, | |
| "warm_up_perc": 1, | |
| "learning_rate": 2e-05, | |
| "loss_type": "supcon", | |
| "val_perc": 0.2, | |
| "wandb_names": { | |
| "project": "linkage", | |
| "id": "econabhishek", | |
| "run": "linkage_un_data_fr_fine_industry", | |
| "entity": "econabhishek" | |
| }, | |
| "add_pooling_layer": false, | |
| "large_val": true, | |
| "eval_steps_perc": 0.5, | |
| "test_at_end": true, | |
| "save_val_test_pickles": true, | |
| "val_query_prop": 0.5, | |
| "loss_params": {}, | |
| "warmup_perc": 0.1, | |
| "eval_type": "retrieval", | |
| "training_dataset": "dataframe", | |
| "base_model_path": "dangvantuan/sentence-camembert-large", | |
| "best_model_path": "models/linkage_un_data_fr_fine_industry" | |
| } |