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Day2 – AI Model by Kamer | AlphaNeural AI
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Kamer
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Day2
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transformers
pytorch
bert
text-classification
generated_from_trainer
nlpaueb/legal-bert-base-uncased
finetune
cc-by-sa-4.0
autotrain_compatible
endpoints_compatible
us
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Day2
This model is a fine-tuned version of
nlpaueb/legal-bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
eval_loss: 0.4956
eval_Accuracy: 0.9035
eval_F1_macro: 0.5229
eval_F1_class_0: 0.0
eval_F1_class_1: 0.0
eval_F1_class_2: 0.9289
eval_F1_class_3: 0.6667
eval_F1_class_4: 0.9910
eval_F1_class_5: 0.6667
eval_F1_class_6: 0.0
eval_F1_class_7: 0.5
eval_F1_class_8: 0.0
eval_F1_class_9: 0.0
eval_F1_class_10: 0.0
eval_F1_class_11: 0.9
eval_F1_class_12: 0.6
eval_F1_class_13: 0.9645
eval_F1_class_14: 0.7500
eval_F1_class_15: 0.8667
eval_F1_class_16: 0.9302
eval_F1_class_17: 1.0
eval_F1_class_18: 0.8605
eval_F1_class_19: 0.6667
eval_F1_class_20: 0.9508
eval_F1_class_21: 0.7692
eval_F1_class_22: 0.0
eval_F1_class_23: 0.6667
eval_F1_class_24: 0.8333
eval_F1_class_25: 0.5714
eval_F1_class_26: 0.9231
eval_F1_class_27: 0.9828
eval_F1_class_28: 0.0
eval_F1_class_29: 0.9500
eval_F1_class_30: 0.0
eval_F1_class_31: 0.0
eval_F1_class_32: 0.5
eval_F1_class_33: 0.5
eval_F1_class_34: 0.8571
eval_F1_class_35: 0.8547
eval_F1_class_36: 0.8727
eval_F1_class_37: 0.5
eval_F1_class_38: 0.8837
eval_F1_class_39: 0.7619
eval_F1_class_40: 0.0
eval_F1_class_41: 0.4444
eval_F1_class_42: 0.0
eval_F1_class_43: 0.0
eval_F1_class_44: 0.0
eval_F1_class_45: 0.7500
eval_F1_class_46: 0.3333
eval_F1_class_47: 0.7556
eval_F1_class_48: 0.8679
eval_F1_class_49: 1.0
eval_F1_class_50: 0.8571
eval_F1_class_51: 0.0
eval_F1_class_52: 0.0
eval_F1_class_53: 0.8
eval_F1_class_54: 0.4
eval_F1_class_55: 0.0
eval_F1_class_56: 0.9082
eval_F1_class_57: 0.0
eval_F1_class_58: 0.6667
eval_F1_class_59: 1.0
eval_F1_class_60: 0.0
eval_F1_class_61: 0.0
eval_F1_class_62: 0.9747
eval_F1_class_63: 0.0
eval_F1_class_64: 0.8966
eval_F1_class_65: 1.0
eval_F1_class_66: 0.8
eval_F1_class_67: 0.0
eval_F1_class_68: 0.0
eval_F1_class_69: 0.0
eval_F1_class_70: 1.0
eval_runtime: 61.7038
eval_samples_per_second: 32.235
eval_steps_per_second: 2.026
epoch: 6.64
step: 3300
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
Framework versions
Transformers 4.32.0
Pytorch 2.0.1+cu117
Datasets 2.14.4
Tokenizers 0.13.3
