roberta no year from scratch better finetuning

roberta_no_year_from_scratch/04_predict.py

@@ -3,12 +3,12 @@ from config import LABELS_LIST, MODEL
 from transformers import AutoTokenizer
 from tqdm import tqdm
 
-device = 'cpu'
-
+device = 'cuda'
+model_path= './roberta-ireland'
 
 from transformers import AutoModelForSequenceClassification
 
-model = AutoModelForSequenceClassification.from_pretrained('test_trainer/checkpoint-620000/')
+model = AutoModelForSequenceClassification.from_pretrained(model_path).cuda()
 tokenizer = AutoTokenizer.from_pretrained(MODEL)
 
 for dataset in ('dev-0', 'test-A'):

roberta_no_year_from_scratch/run.sh

@@ -0,0 +1,12 @@
+python run_glue.py   --model_name_or_path roberta-base \
+     	--train_file ../train/huggingface_format.csv \
+       	--validation_file /media/kuba/ssdsam/gonito/ireland-news/dev-0/huggingface_format.csv \
+   	--do_train \
+ 	--max_seq_length 64 \
+     	--per_device_train_batch_size 32 \
+     	--learning_rate 2e-5 \
+     	--num_train_epochs 3 \
+     	--output_dir ./roberta-ireland \
+        --save_steps=10000 \
+	--eval_steps=10000 \
+	--evaluation_strategy steps