init

training_scripts/script.sh

@@ -9,7 +9,7 @@ python finetune_t5.py -m cardiffnlp/mt5-small-tweet-topic-multi-en-2022 --datase
 
 
 
-python finetune_t5.py --dataset-name es --low-cpu-mem-usage --model-alias mt5-small-tweet-topic-multi-es --model-organization cardiffnlp --use-auth-token
+python finetune_t5.py --dataset-name es --low-cpu-mem-usage --model-alias mt5-small-tweet-topic-multi-es --model-organization cardiffnlp --use-auth-token --skip-train --skip-test
 python finetune_t5.py --dataset-name en --low-cpu-mem-usage --model-alias mt5-small-tweet-topic-multi-en --model-organization cardiffnlp --use-auth-token
 
 python finetune_t5.py --dataset-name ja --low-cpu-mem-usage --model-alias mt5-small-tweet-topic-multi-ja --model-organization cardiffnlp --use-auth-token

tweet_topic_multilingual.py

@@ -6,7 +6,7 @@ import datasets
 
 logger = datasets.logging.get_logger(__name__)
 _DESCRIPTION = """[TweetTopicMultilingual](TBA)"""
-_VERSION = "0.0.7"
+_VERSION = "0.0.8"
 _CITATION = """TBA"""
 _HOME_PAGE = "https://cardiffnlp.github.io"
 _NAME = "tweet_topic_multilingual"
@@ -146,7 +146,7 @@ class TweetTopicMultilingual(datasets.GeneratorBasedBuilder):
         if type(filepath) is not List:
             filepath = [filepath]
         for _file in filepath:
-            logger.info("generating examples from = %s", i)
+            logger.info("generating examples from = %s", _file)
             with open(_file, encoding="utf-8") as f:
                 _list = [json.loads(i) for i in f.read().split("\n") if len(i) > 0]
                 for i in _list: