scripts/eval_make_docid_glen_vault.sh

#!/bin/bash

# Path to trained model
MODEL_PATH="logs/model_glen_vault/GLEN_P2_base"

CUDA_VISIBLE_DEVICES=0 \
python examples/glen_phase1/makeid_glen.py \
    --model_name_or_path ${MODEL_PATH} \
    --dataset_name the_vault \
    --test100 0 \
    --id_class t5_bm25_truncate_3 \
    --max_input_length 256 \
    --per_device_eval_batch_size 32 \
    --output_dir ${MODEL_PATH} \
    --tie_word_embeddings True \
    --gen_method greedy \
    --num_return_sequences 1 \
    --tree 1 \
    --overwrite_output_dir