Update lm_finetuning.py

lm_finetuning.py

@@ -1,3 +1,13 @@
+```
+wandb offline
+export WANDB_DISABLED='true'
+export RAY_RESULTS='ray_results'
+python lm_finetuning.py -m "roberta-large" -c "ckpt/roberta_large" --push-to-hub --hf-organization "cardiffnlp" -a "twitter-roberta-base-2019-90m-tweet-topic-multi"
+python lm_finetuning.py -m "roberta-base" -c "ckpt/roberta_base" --push-to-hub --hf-organization "cardiffnlp" -a "twitter-roberta-base-2019-90m-tweet-topic-multi"
+python lm_finetuning.py -m "cardiffnlp/twitter-roberta-base-2019-90m" -c "ckpt/twitter-roberta-base-2019-90m" --push-to-hub --hf-organization "cardiffnlp" -a "twitter-roberta-base-2019-90m-tweet-topic-multi"
+python lm_finetuning.py -m "cardiffnlp/twitter-roberta-base-dec2020" -c "ckpt/twitter-roberta-base-dec2020"
+python lm_finetuning.py -m "cardiffnlp/twitter-roberta-base-dec2021" -c "ckpt/twitter-roberta-base-dec2021"
+```
 import argparse
 import json
 import logging
@@ -55,7 +65,6 @@ def main():
     parser = argparse.ArgumentParser(description='Fine-tuning language model.')
     parser.add_argument('-m', '--model', help='transformer LM', default='roberta-base', type=str)
     parser.add_argument('-d', '--dataset', help='', default='cardiffnlp/tweet_topic_multi', type=str)
-    parser.add_argument('--dataset-name', help='huggingface dataset name', default='citation_intent', type=str)
     parser.add_argument('-l', '--seq-length', help='', default=128, type=int)
     parser.add_argument('--random-seed', help='', default=42, type=int)
     parser.add_argument('--eval-step', help='', default=50, type=int)
@@ -71,7 +80,7 @@ def main():
     opt = parser.parse_args()
     assert opt.summary_file.endswith('.json'), f'`--summary-file` should be a json file {opt.summary_file}'
     # setup data
-    dataset = load_dataset(opt.dataset, opt.dataset_name)
+    dataset = load_dataset(opt.dataset)
     network = internet_connection()
     # setup model
     tokenizer = AutoTokenizer.from_pretrained(opt.model, local_files_only=not network)