Some changes to allow training with kaggle data

train.sh

@@ -1,22 +1,21 @@
 #!/bin/sh
 python -m train \
 	--save_checkpoints_every 10 \
-    --experiment_name "augment_rotate_75_x8" \
+    --experiment_name "basic" \
     --epochs 300 \
 	--optimizer "ADAM" \
-	--lr 0.001 \
+	--lr 0.0001 \
     --batch_size 16 \
-	--dataset_name "processed" \
+	--dataset_name "GoogleWLASL" \
 	--training_set_path "spoter_train.csv" \
 	--validation_set_path "spoter_test.csv" \
 	--vector_length 32 \
 	--epoch_iters -1 \
-	--scheduler_factor 0 \
-	--hard_triplet_mining "in_batch" \
+	--scheduler_factor 0.2 \
+	--hard_triplet_mining "None" \
 	--filter_easy_triplets \
-	--triplet_loss_margin 1 \
+	--triplet_loss_margin 2 \
 	--dropout 0.2 \
-	--augmentations_prob=0.75 \
-	--hard_mining_scheduler_triplets_threshold=0 \
-	--normalize_embeddings \
-    --num_classes 100 \
+    --tracker=clearml \
+    --dataset_loader=clearml \
+	--dataset_project="SpoterEmbedding"