hf roberta base regression layer on top

hf_roberta_base/03_train_pytorch_regression.py

@@ -9,7 +9,7 @@ from transformers import get_scheduler
 import torch
 from tqdm.auto import tqdm
 
-BATCH_SIZE = 1
+BATCH_SIZE = 24
 EARLY_STOPPING = 3
 WARMUP_STEPS = 10_000
 
@@ -38,7 +38,7 @@ model = AutoModelForSequenceClassification.from_pretrained(MODEL, num_labels=1)
 optimizer = AdamW(model.parameters(), lr=1e-6)
 
 
-num_epochs = 1
+num_epochs = 15
 num_training_steps = num_epochs * len(train_dataloader)
 lr_scheduler = get_scheduler(
     "linear",

hf_roberta_base/config.py

@@ -1,4 +1,4 @@
 #MODEL = '/home/wmi/RoBERTa/without_date/checkpoint-1325000'
 MODEL = 'roberta-base'
-TEST=True
+TEST=False