Tokenizer: bert-base-uncased Model: bert-base-uncased
	Train size: 80 Test size: 20


		-------------RUN 1-----------
Sep token: 102
BOS token: 101
			------------EPOCH 1---------------
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			------------EPOCH 6---------------
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		-------------RUN 2-----------
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			------------EPOCH 1---------------
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			------------EPOCH 10---------------
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			------------EPOCH 13---------------
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		-------------RUN 3-----------
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			------------EPOCH 1---------------
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			------------EPOCH 5---------------
Evaluating
Evaluating
Evaluating
Evaluating
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		-------------RUN 4-----------
Sep token: 102
BOS token: 101
			------------EPOCH 1---------------
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			------------EPOCH 5---------------
Evaluating
Evaluating
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		-------------RUN 5-----------
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			------------EPOCH 1---------------
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	Train size: 50 Test size: 50


		-------------RUN 1-----------
Sep token: 102
BOS token: 101
			------------EPOCH 1---------------
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Loss: tensor(1.7624, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 3---------------
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			------------EPOCH 6---------------
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Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 9---------------
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Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
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			------------EPOCH 11---------------
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			------------EPOCH 12---------------
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			------------EPOCH 13---------------
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			------------EPOCH 14---------------
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Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 18---------------
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Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 19---------------
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Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
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		-------------RUN 2-----------
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			------------EPOCH 1---------------
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Loss: tensor(0.7835, device='cuda:0', grad_fn=<DivBackward0>)
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			------------EPOCH 7---------------
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Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 8---------------
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Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 9---------------
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Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 10---------------
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Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 11---------------
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Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 12---------------
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			------------EPOCH 16---------------
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			------------EPOCH 19---------------
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Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
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		-------------RUN 3-----------
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			------------EPOCH 1---------------
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Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 5---------------
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			------------EPOCH 6---------------
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Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 8---------------
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			------------EPOCH 9---------------
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Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 11---------------
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			------------EPOCH 12---------------
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Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 17---------------
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			------------EPOCH 18---------------
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			------------EPOCH 20---------------
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		-------------RUN 4-----------
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BOS token: 101
			------------EPOCH 1---------------
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Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 6---------------
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Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 7---------------
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			------------EPOCH 11---------------
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Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
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			------------EPOCH 12---------------
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Loss: tensor(9.5673e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 19---------------
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Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 20---------------
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		-------------RUN 5-----------
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			------------EPOCH 1---------------
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				 {'precision': {'support': 0.7597911227154047, 'agreement': 0.5737704918032787, 'direct_attack': 0.14076246334310852, 'undercutter_attack': 0.12411347517730496, 'partial': 0.17142857142857143}, 'recall': {'support': 0.6539325842696629, 'agreement': 0.1483050847457627, 'direct_attack': 0.3582089552238806, 'undercutter_attack': 0.23809523809523808, 'partial': 0.10619469026548672}, 'f1': {'support': 0.7028985507246377, 'agreement': 0.23569023569023567, 'direct_attack': 0.20210526315789473, 'undercutter_attack': 0.16317016317016317, 'partial': 0.13114754098360654}, 'support': {'support': 890, 'agreement': 236, 'direct_attack': 134, 'undercutter_attack': 147, 'partial': 113}, 'micro_avg': {'precision': 0.46842105263157896, 'recall': 0.46842105263157896, 'f1': 0.46842105263157896, 'support': None}, 'macro_avg': {'precision': 0.3539732248935337, 'recall': 0.3009473105200062, 'f1': 0.28700235074530756, 'support': None}, 'weighted_avg': {'precision': 0.5711198781531269, 'recall': 0.46842105263157896, 'f1': 0.4915068402290411, 'support': None}}
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Loss: tensor(0.4826, device='cuda:0', grad_fn=<DivBackward0>)
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Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 7---------------
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Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 8---------------
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Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 9---------------
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			------------EPOCH 11---------------
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			------------EPOCH 12---------------
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			------------EPOCH 13---------------
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			------------EPOCH 14---------------
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				 {'precision': {'support': 0.737006237006237, 'agreement': 0.5344827586206896, 'direct_attack': 0.13793103448275862, 'undercutter_attack': 0.14049586776859505, 'partial': 0.23636363636363636}, 'recall': {'support': 0.7966292134831461, 'agreement': 0.13135593220338984, 'direct_attack': 0.208955223880597, 'undercutter_attack': 0.23129251700680273, 'partial': 0.11504424778761062}, 'f1': {'support': 0.7656587473002161, 'agreement': 0.21088435374149664, 'direct_attack': 0.1661721068249258, 'undercutter_attack': 0.17480719794344474, 'partial': 0.15476190476190477}, 'support': {'support': 890, 'agreement': 236, 'direct_attack': 134, 'undercutter_attack': 147, 'partial': 113}, 'micro_avg': {'precision': 0.5361842105263158, 'recall': 0.5361842105263158, 'f1': 0.5361842105263158, 'support': None}, 'macro_avg': {'precision': 0.3572559068483833, 'recall': 0.2966554268723093, 'f1': 0.2944568621143976, 'support': None}, 'weighted_avg': {'precision': 0.5578409368827617, 'recall': 0.5361842105263158, 'f1': 0.5241163212042811, 'support': None}}
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Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
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Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1212e-05, device='cuda:0', grad_fn=<DivBackward0>)
