diff --git "a/nohup.out" "b/nohup.out"
new file mode 100644--- /dev/null
+++ "b/nohup.out"
@@ -0,0 +1,613 @@
+Some weights of MultiTaskDistilBert were not initialized from the model checkpoint at distilbert-base-uncased and are newly initialized: ['classifier_interv.bias', 'classifier_interv.weight', 'classifier_main.bias', 'classifier_main.weight', 'classifier_priority.bias', 'classifier_priority.weight', 'classifier_sub.bias', 'classifier_sub.weight', 'pre_classifier.bias', 'pre_classifier.weight']
+You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
+Using device: cuda
+                          category                main_category
+0               Drug/Alcohol Abuse       Advice and Counselling
+1                     Homelessness       Advice and Counselling
+2                         HIV/AIDS       Advice and Counselling
+3  Relationships (Student/Teacher)       Advice and Counselling
+4                      Foster Care  Child Maintenance & Custody
+
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+{'loss': 7.4076, 'grad_norm': 7.764742374420166, 'learning_rate': 1.939806412583182e-05, 'epoch': 0.36}
+{'loss': 6.9057, 'grad_norm': 8.161060333251953, 'learning_rate': 1.9095583787053844e-05, 'epoch': 0.54}
+{'loss': 6.4695, 'grad_norm': 8.871325492858887, 'learning_rate': 1.8793103448275863e-05, 'epoch': 0.73}
+{'loss': 6.0925, 'grad_norm': 9.516924858093262, 'learning_rate': 1.8490623109497885e-05, 'epoch': 0.91}
+
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 98%|█████████▊| 61/62 [00:05<00:00, 11.62it/s]Traceback (most recent call last):
+  File "/home/rogendo/Work/Training/multitask_classifier_pipeline.py", line 413, in <module>
+    trainer.train()
+  File "/home/rogendo/chl_scratch/mcreativity/lib/python3.12/site-packages/transformers/trainer.py", line 2240, in train
+    return inner_training_loop(
+           ^^^^^^^^^^^^^^^^^^^^
+  File "/home/rogendo/chl_scratch/mcreativity/lib/python3.12/site-packages/transformers/trainer.py", line 2656, in _inner_training_loop
+    self._maybe_log_save_evaluate(
+  File "/home/rogendo/chl_scratch/mcreativity/lib/python3.12/site-packages/transformers/trainer.py", line 3095, in _maybe_log_save_evaluate
+    metrics = self._evaluate(trial, ignore_keys_for_eval)
+              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/rogendo/chl_scratch/mcreativity/lib/python3.12/site-packages/transformers/trainer.py", line 3044, in _evaluate
+    metrics = self.evaluate(ignore_keys=ignore_keys_for_eval)
+              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/rogendo/chl_scratch/mcreativity/lib/python3.12/site-packages/transformers/trainer.py", line 4173, in evaluate
+    output = eval_loop(
+             ^^^^^^^^^^
+  File "/home/rogendo/chl_scratch/mcreativity/lib/python3.12/site-packages/transformers/trainer.py", line 4463, in evaluation_loop
+    metrics = self.compute_metrics(
+              ^^^^^^^^^^^^^^^^^^^^^
+  File "/home/rogendo/Work/Training/multitask_classifier_pipeline.py", line 319, in compute_metrics
+    add_task_metrics("main", labels_main, preds_main)
+  File "/home/rogendo/Work/Training/multitask_classifier_pipeline.py", line 312, in add_task_metrics
+    precision, recall, f1, _ = precision_recall_fscore_support(labels, preds, average='weighted', zero_division=0)
+                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+NameError: name 'precision_recall_fscore_support' is not defined
+🏃 View run ./results at: http://192.168.8.18:5000/#/experiments/13/runs/90f04209b8fb49cd9f7d77e8422f2cbe
+🧪 View experiment at: http://192.168.8.18:5000/#/experiments/13
+
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+
                                               Some weights of MultiTaskDistilBert were not initialized from the model checkpoint at distilbert-base-uncased and are newly initialized: ['classifier_interv.bias', 'classifier_interv.weight', 'classifier_main.bias', 'classifier_main.weight', 'classifier_priority.bias', 'classifier_priority.weight', 'classifier_sub.bias', 'classifier_sub.weight', 'pre_classifier.bias', 'pre_classifier.weight']
+You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
+Using device: cuda
+                          category                main_category
+0               Drug/Alcohol Abuse       Advice and Counselling
+1                     Homelessness       Advice and Counselling
+2                         HIV/AIDS       Advice and Counselling
+3  Relationships (Student/Teacher)       Advice and Counselling
+4                      Foster Care  Child Maintenance & Custody
+
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  8%|▊         | 551/6612 [02:42<26:53,  3.76it/s]{'loss': 7.9493, 'grad_norm': 6.7841339111328125, 'learning_rate': 1.9700544464609802e-05, 'epoch': 0.18}
+{'loss': 7.6243, 'grad_norm': 6.271908283233643, 'learning_rate': 1.939806412583182e-05, 'epoch': 0.36}
+{'loss': 7.1546, 'grad_norm': 8.516470909118652, 'learning_rate': 1.9095583787053844e-05, 'epoch': 0.54}
+{'loss': 6.6532, 'grad_norm': 8.8213472366333, 'learning_rate': 1.8793103448275863e-05, 'epoch': 0.73}
+{'loss': 6.2489, 'grad_norm': 9.666668891906738, 'learning_rate': 1.8490623109497885e-05, 'epoch': 0.91}
+
+
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100%|██████████| 62/62 [00:05<00:00, 13.22it/s]
                                                  
+
                                               

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+
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+
                                               
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+{'loss': 4.2089, 'grad_norm': 12.501510620117188, 'learning_rate': 1.516333938294011e-05, 'epoch': 2.9}
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+{'loss': 4.0599, 'grad_norm': 11.418658256530762, 'learning_rate': 1.4860859044162131e-05, 'epoch': 3.09}
+{'loss': 3.9068, 'grad_norm': 13.876314163208008, 'learning_rate': 1.455837870538415e-05, 'epoch': 3.27}
+{'loss': 3.9367, 'grad_norm': 16.714431762695312, 'learning_rate': 1.4255898366606171e-05, 'epoch': 3.45}
+{'loss': 3.8531, 'grad_norm': 11.18697452545166, 'learning_rate': 1.3953418027828192e-05, 'epoch': 3.63}
+{'loss': 3.8714, 'grad_norm': 10.831789016723633, 'learning_rate': 1.3650937689050213e-05, 'epoch': 3.81}
+{'loss': 3.8414, 'grad_norm': 16.59636116027832, 'learning_rate': 1.3348457350272232e-05, 'epoch': 3.99}
+
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+{'loss': 3.2583, 'grad_norm': 29.03419303894043, 'learning_rate': 1.002117362371446e-05, 'epoch': 5.99}
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+{'loss': 2.9628, 'grad_norm': 18.006244659423828, 'learning_rate': 9.718693284936481e-06, 'epoch': 6.17}
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+{'loss': 3.0037, 'grad_norm': 28.830854415893555, 'learning_rate': 8.508771929824563e-06, 'epoch': 6.9}
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+{'loss': 2.755, 'grad_norm': 29.779342651367188, 'learning_rate': 6.6938898971566855e-06, 'epoch': 7.99}
+
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+{'loss': 2.3358, 'grad_norm': 22.808115005493164, 'learning_rate': 1.854204476709014e-06, 'epoch': 10.89}
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100%|██████████| 6612/6612 [34:01<00:00,  2.80it/s]{'eval_avg_acc': 0.6570480081716037, 'eval_avg_precision': 0.6395819948517396, 'eval_avg_recall': 0.6570480081716037, 'eval_avg_f1': 0.6421489882551977, 'eval_main_acc': 0.710929519918284, 'eval_main_precision': 0.7010464178493915, 'eval_main_recall': 0.710929519918284, 'eval_main_f1': 0.7036037691452541, 'eval_sub_acc': 0.5771195097037793, 'eval_sub_precision': 0.5856504090830769, 'eval_sub_recall': 0.5771195097037793, 'eval_sub_f1': 0.5730196670911161, 'eval_interv_acc': 0.6772216547497446, 'eval_interv_precision': 0.6541816061478233, 'eval_interv_recall': 0.6772216547497446, 'eval_interv_f1': 0.6629101223677621, 'eval_priority_acc': 0.6629213483146067, 'eval_priority_precision': 0.6174495463266665, 'eval_priority_recall': 0.6629213483146067, 'eval_priority_f1': 0.6290623944166588, 'eval_runtime': 5.2994, 'eval_samples_per_second': 184.739, 'eval_steps_per_second': 11.7, 'epoch': 11.0}
+{'loss': 2.2766, 'grad_norm': 31.797069549560547, 'learning_rate': 1.5517241379310346e-06, 'epoch': 11.07}
+{'loss': 2.1794, 'grad_norm': 27.20286750793457, 'learning_rate': 1.249243799153055e-06, 'epoch': 11.25}
+{'loss': 2.3038, 'grad_norm': 20.983129501342773, 'learning_rate': 9.467634603750757e-07, 'epoch': 11.43}
+{'loss': 2.2522, 'grad_norm': 27.29282569885254, 'learning_rate': 6.442831215970963e-07, 'epoch': 11.62}
+{'loss': 2.2279, 'grad_norm': 21.053974151611328, 'learning_rate': 3.418027828191168e-07, 'epoch': 11.8}
+{'loss': 2.2345, 'grad_norm': 27.998193740844727, 'learning_rate': 3.932244404113733e-08, 'epoch': 11.98}
+
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+{'eval_avg_acc': 0.6547497446373851, 'eval_avg_precision': 0.6391902296225433, 'eval_avg_recall': 0.6547497446373851, 'eval_avg_f1': 0.6415252203801691, 'eval_main_acc': 0.7119509703779366, 'eval_main_precision': 0.7074330551128643, 'eval_main_recall': 0.7119509703779366, 'eval_main_f1': 0.7057122312576722, 'eval_sub_acc': 0.5760980592441267, 'eval_sub_precision': 0.5811512455815515, 'eval_sub_recall': 0.5760980592441267, 'eval_sub_f1': 0.5709057727596365, 'eval_interv_acc': 0.6731358529111338, 'eval_interv_precision': 0.6509780211158839, 'eval_interv_recall': 0.6731358529111338, 'eval_interv_f1': 0.6599756835156314, 'eval_priority_acc': 0.6578140960163432, 'eval_priority_precision': 0.6171985966798736, 'eval_priority_recall': 0.6578140960163432, 'eval_priority_f1': 0.6295071939877362, 'eval_runtime': 7.6172, 'eval_samples_per_second': 128.526, 'eval_steps_per_second': 8.14, 'epoch': 12.0}
+{'train_runtime': 2049.9321, 'train_samples_per_second': 51.572, 'train_steps_per_second': 3.225, 'train_loss': 3.548401413725422, 'epoch': 12.0}
+🏃 View run ./results at: http://192.168.8.18:5000/#/experiments/13/runs/487af20bf3b64c6f94cdb6e108da93d8
+🧪 View experiment at: http://192.168.8.18:5000/#/experiments/13
+
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+🏃 View run skittish-fly-114 at: http://192.168.8.18:5000/#/experiments/13/runs/0b4607ea961e44ada8f20104843966c6
+🧪 View experiment at: http://192.168.8.18:5000/#/experiments/13