init

training_scripts/finetune_t5.py

@@ -137,7 +137,7 @@ def train(
 
     if not skip_train:
         lr = [1e-6, 1e-5, 1e-4] if lr is None else lr
-        batch = [64] if not batch else batch
+        batch = [32] if not batch else batch
         epoch = [3, 5] if not epoch else epoch
         eval_batch_size = min(batch) if not eval_batch_size else eval_batch_size
         for n, (lr_tmp, batch_tmp, epoch_tmp) in enumerate(product(lr, batch, epoch)):

training_scripts/script.sh

@@ -1,6 +1,8 @@
-python finetune_t5.py --dataset-name ja --low-cpu-mem-usage --model-alias mt5-small-tweet-topic-ja --model-organization cardiffnlp --skip-upload
-python finetune_t5.py --dataset-name gr --low-cpu-mem-usage --model-alias mt5-small-tweet-topic-gr --model-organization cardiffnlp
-python finetune_t5.py --dataset-name es --low-cpu-mem-usage --model-alias mt5-small-tweet-topic-es --model-organization cardiffnlp
-python finetune_t5.py --dataset-name en --low-cpu-mem-usage --model-alias mt5-small-tweet-topic-en --model-organization cardiffnlp
+
+
+python finetune_t5.py --dataset-name ja --low-cpu-mem-usage --model-alias mt5-small-tweet-topic-multi-ja --model-organization cardiffnlp
+python finetune_t5.py --dataset-name gr --low-cpu-mem-usage --model-alias mt5-small-tweet-topic-multi-gr --model-organization cardiffnlp
+python finetune_t5.py --dataset-name es --low-cpu-mem-usage --model-alias mt5-small-tweet-topic-multi-es --model-organization cardiffnlp
+python finetune_t5.py --dataset-name en --low-cpu-mem-usage --model-alias mt5-small-tweet-topic-multi-en --model-organization cardiffnlp