init

training_scripts/finetune_t5.py

@@ -8,6 +8,7 @@ import logging
 import os
 import argparse
 import gc
+from glob import glob
 from typing import List, Set, Dict
 from shutil import copyfile
 from statistics import mean
@@ -15,6 +16,7 @@ from itertools import product
 
 import torch
 import transformers
+import numba
 from datasets import load_dataset
 from transformers import Seq2SeqTrainer, Seq2SeqTrainingArguments, pipeline
 from huggingface_hub import Repository
@@ -176,6 +178,14 @@ def train(
             del model
             gc.collect()
             torch.cuda.empty_cache()
+            numba.cuda.get_current_device().reset()
+
+        model_score = {}
+        for eval_file in glob(f"{output_dir}/model_*/eval_result.json"):
+            with open(eval_file) as f:
+                model_score[os.path.dirname(eval_file)] = json.load(f)['eval_f1']
+        best_model = max(model_score, key=model_score.get)
+
     else:
         logging.info('skip hyperparameter search & model training (already done)')