Loading pytorch-gpu/py3/2.1.1 Loading requirement: cuda/11.8.0 nccl/2.18.5-1-cuda cudnn/8.7.0.84-cuda gcc/8.5.0 openmpi/4.1.5-cuda intel-mkl/2020.4 magma/2.7.1-cuda sox/14.4.2 sparsehash/2.0.3 libjpeg-turbo/2.1.3 ffmpeg/4.4.4 + HF_DATASETS_OFFLINE=1 + TRANSFORMERS_OFFLINE=1 + python3 OnlyGeneralTokenizer.py Checking label assignment: Domain: Mathematics Categories: math.OA Abstract: a result of akemann anderson and pedersen states that if a sequence of pure states of a calgebra a a... Domain: Computer Science Categories: cs.PL Abstract: a rigid loop is a forloop with a counter not accessible to the loop body or any other part of a prog... Domain: Physics Categories: physics.gen-ph Abstract: fractional calculus and qdeformed lie algebras are closely related both concepts expand the scope of... Domain: Chemistry Categories: quant-ph nlin.CD Abstract: we study scarring phenomena in open quantum systems we show numerical evidence that individual reson... Domain: Statistics Categories: stat.ME Abstract: chess and chance are seemingly strange bedfellows luck andor randomness have no apparent role in mov... Domain: Biology Categories: q-bio.MN Abstract: in the simplest view of transcriptional regulation the expression of a gene is turned on or off by c... /linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/transformers/tokenization_utils_base.py:2057: FutureWarning: Calling BertTokenizer.from_pretrained() with the path to a single file or url is deprecated and won't be possible anymore in v5. Use a model identifier or the path to a directory instead. warnings.warn( Training with All Cluster tokenizer: Vocabulary size: 16005 Could not load pretrained weights from /linkhome/rech/genrug01/uft12cr/bert_Model. Starting with random weights. Error: It looks like the config file at '/linkhome/rech/genrug01/uft12cr/bert_Model/config.json' is not a valid JSON file. Initialized model with vocabulary size: 16005 /gpfsdswork/projects/rech/fmr/uft12cr/finetuneAli/OnlyGeneralTokenizer.py:172: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead. scaler = amp.GradScaler() Batch 0: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 /gpfsdswork/projects/rech/fmr/uft12cr/finetuneAli/OnlyGeneralTokenizer.py:192: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead. with amp.autocast(): Batch 100: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 200: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 300: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 400: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 500: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 600: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 700: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 800: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 900: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Epoch 1/3: Val Accuracy: 0.7549, Val F1: 0.6896 Batch 0: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 /gpfsdswork/projects/rech/fmr/uft12cr/finetuneAli/OnlyGeneralTokenizer.py:192: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead. with amp.autocast(): Batch 100: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 200: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 300: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 400: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 500: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 600: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 700: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 800: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 900: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Epoch 2/3: Val Accuracy: 0.7473, Val F1: 0.7221 Batch 0: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 /gpfsdswork/projects/rech/fmr/uft12cr/finetuneAli/OnlyGeneralTokenizer.py:192: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead. with amp.autocast(): Batch 100: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 200: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 300: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 400: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 500: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 600: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 700: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 800: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Batch 900: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 16003 Vocab size: 16005 Epoch 3/3: Val Accuracy: 0.8081, Val F1: 0.7870 Test Results for All Cluster tokenizer: Accuracy: 0.8084 F1 Score: 0.7874 AUC-ROC: 0.8421 Training with Final tokenizer: Vocabulary size: 15253 Could not load pretrained weights from /linkhome/rech/genrug01/uft12cr/bert_Model. Starting with random weights. Error: It looks like the config file at '/linkhome/rech/genrug01/uft12cr/bert_Model/config.json' is not a valid JSON file. Initialized model with vocabulary size: 15253 /gpfsdswork/projects/rech/fmr/uft12cr/finetuneAli/OnlyGeneralTokenizer.py:172: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead. scaler = amp.GradScaler() Batch 0: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 /gpfsdswork/projects/rech/fmr/uft12cr/finetuneAli/OnlyGeneralTokenizer.py:192: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead. with amp.autocast(): Batch 100: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 200: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 300: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 400: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 500: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 600: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 700: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 800: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 900: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Epoch 1/3: Val Accuracy: 0.7096, Val F1: 0.6564 Batch 0: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 /gpfsdswork/projects/rech/fmr/uft12cr/finetuneAli/OnlyGeneralTokenizer.py:192: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead. with amp.autocast(): Batch 100: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 200: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 300: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 400: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 500: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 600: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 700: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 800: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 900: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Epoch 2/3: Val Accuracy: 0.7246, Val F1: 0.6799 Batch 0: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 /gpfsdswork/projects/rech/fmr/uft12cr/finetuneAli/OnlyGeneralTokenizer.py:192: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead. with amp.autocast(): Batch 100: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 200: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 300: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 400: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 500: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 600: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 700: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 800: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Batch 900: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 15252 Vocab size: 15253 Epoch 3/3: Val Accuracy: 0.7661, Val F1: 0.7440 Test Results for Final tokenizer: Accuracy: 0.7661 F1 Score: 0.7441 AUC-ROC: 0.8256 Training with General tokenizer: Vocabulary size: 30522 Could not load pretrained weights from /linkhome/rech/genrug01/uft12cr/bert_Model. Starting with random weights. Error: It looks like the config file at '/linkhome/rech/genrug01/uft12cr/bert_Model/config.json' is not a valid JSON file. Initialized model with vocabulary size: 30522 /gpfsdswork/projects/rech/fmr/uft12cr/finetuneAli/OnlyGeneralTokenizer.py:172: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead. scaler = amp.GradScaler() Batch 0: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29464 Vocab size: 30522 /gpfsdswork/projects/rech/fmr/uft12cr/finetuneAli/OnlyGeneralTokenizer.py:192: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead. with amp.autocast(): Batch 100: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29536 Vocab size: 30522 Batch 200: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29464 Vocab size: 30522 Batch 300: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29402 Vocab size: 30522 Batch 400: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29535 Vocab size: 30522 Batch 500: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29494 Vocab size: 30522 Batch 600: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29454 Vocab size: 30522 Batch 700: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29413 Vocab size: 30522 Batch 800: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 28993 Vocab size: 30522 Batch 900: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29602 Vocab size: 30522 Epoch 1/3: Val Accuracy: 0.7601, Val F1: 0.7079 Batch 0: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29413 Vocab size: 30522 /gpfsdswork/projects/rech/fmr/uft12cr/finetuneAli/OnlyGeneralTokenizer.py:192: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead. with amp.autocast(): Batch 100: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29413 Vocab size: 30522 Batch 200: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29464 Vocab size: 30522 Batch 300: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29098 Vocab size: 30522 Batch 400: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29339 Vocab size: 30522 Batch 500: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29560 Vocab size: 30522 Batch 600: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29464 Vocab size: 30522 Batch 700: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29536 Vocab size: 30522 Batch 800: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29458 Vocab size: 30522 Batch 900: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29413 Vocab size: 30522 Epoch 2/3: Val Accuracy: 0.8002, Val F1: 0.7716 Batch 0: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29536 Vocab size: 30522 /gpfsdswork/projects/rech/fmr/uft12cr/finetuneAli/OnlyGeneralTokenizer.py:192: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead. with amp.autocast(): Batch 100: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29413 Vocab size: 30522 Batch 200: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29605 Vocab size: 30522 Batch 300: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29464 Vocab size: 30522 Batch 400: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29237 Vocab size: 30522 Batch 500: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29292 Vocab size: 30522 Batch 600: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29461 Vocab size: 30522 Batch 700: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29536 Vocab size: 30522 Batch 800: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29536 Vocab size: 30522 Batch 900: input_ids shape: torch.Size([16, 256]) attention_mask shape: torch.Size([16, 256]) labels shape: torch.Size([16]) input_ids max value: 29566 Vocab size: 30522 Epoch 3/3: Val Accuracy: 0.8160, Val F1: 0.7785 Test Results for General tokenizer: Accuracy: 0.8160 F1 Score: 0.7785 AUC-ROC: 0.8630 Summary of Results: All Cluster Tokenizer: Accuracy: 0.8084 F1 Score: 0.7874 AUC-ROC: 0.8421 Final Tokenizer: Accuracy: 0.7661 F1 Score: 0.7441 AUC-ROC: 0.8256 General Tokenizer: Accuracy: 0.8160 F1 Score: 0.7785 AUC-ROC: 0.8630 Class distribution in training set: Class Biology: 439 samples Class Chemistry: 454 samples Class Computer Science: 1358 samples Class Mathematics: 9480 samples Class Physics: 2733 samples Class Statistics: 200 samples