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roberta_year_as_token_better_finetunning/config.py
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roberta_year_as_token_better_finetunning/config.py
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LABELS_DICT = {'news':0,
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'sport':1,
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'business':2,
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'opinion':3,
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'culture':4,
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'lifestyle':5,
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'removed':6}
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LABELS_LIST = ['news',
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'sport',
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'business',
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'opinion',
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'culture',
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'lifestyle',
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'removed']
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MODEL = 'roberta-base'
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python run_glue.py --model_name_or_path roberta-base --train_file /media/kuba/ssdsam/gonito/ireland-news/train/huggingface_format_year.csv --validation_file /media/kuba/ssdsam/gonito/ireland-news/dev-0/huggingface_format_year.csv --do_train --do_eval --max_seq_length 64 --per_device_train_batch_size 32 --learning_rate 2e-5 --num_train_epochs 3 --save_steps=5000 --eval_steps=5000 --evaluation_strategy steps --output_dir ./roberta-ireland
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python run_glue.py --model_name_or_path roberta-base --train_file ../train/huggingface_format_year.csv --validation_file ../dev-0/huggingface_format_year.csv --do_train --do_eval --max_seq_length 64 --per_device_train_batch_size 32 --learning_rate 2e-5 --num_train_epochs 3 --save_steps=5000 --eval_steps=5000 --evaluation_strategy steps --output_dir ./roberta-ireland
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