Evaluation with .mdl
file is given clearly on their repo:
# P@1,100
python retrieval_train.py \
--batch-size 256 \
--bert-dim 300 \
--cuda \
--dataset-name empchat \
--dict-max-words 250000 \
--display-iter 100 \
--embeddings None \
--empchat-folder ${EMPATHETIC_DIALOGUES_DATA_FOLDER} \
--max-hist-len 4 \
--model bert \
--model-dir ${EVAL_SAVE_FOLDER} \
--model-name model \
--optimizer adamax \
--pretrained ${TRAIN_SAVE_FOLDER}/model.mdl \
--reactonly
# BLEU (EmpatheticDialogues context/candidates)
python retrieval_eval_bleu.py \
--bleu-dict ${PATH_TO_MODEL_WITH_TRANSFORMER_DICT} \
--empchat-cands \
--empchat-folder ${EMPATHETIC_DIALOGUES_DATA_FOLDER} \
--max-hist-len 4 \
--model ${TRAIN_SAVE_FOLDER}/model.mdl \
--name model \
--output-folder ${EVAL_SAVE_FOLDER} \
--reactonly \
--task empchat
Yes, you can use any of the 6 models.
wget https://dl.fbaipublicfiles.com/parlai/empatheticdialogues/models/normal_transformer_pretrained.mdl # Normal Transformer, pretrained
wget https://dl.fbaipublicfiles.com/parlai/empatheticdialogues/models/normal_transformer_finetuned.mdl # Normal Transformer, fine-tuned
wget https://dl.fbaipublicfiles.com/parlai/empatheticdialogues/models/bert_pretrained.mdl # BERT, pretrained
wget https://dl.fbaipublicfiles.com/parlai/empatheticdialogues/models/bert_finetuned.mdl # BERT, fine-tuned
wget https://dl.fbaipublicfiles.com/parlai/empatheticdialogues/models/bert_finetuned_emoprepend1.mdl # BERT, fine-tuned (EmoPrepend-1)
wget https://dl.fbaipublicfiles.com/parlai/empatheticdialogues/models/fasttext_empathetic_dialogues.mdl # fastText classifier used for EmoPrepend-1