FlavioNoEng

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: 0.4980
• eval_Accuracy: 0.8841
• eval_F1_macro: 0.7387
• eval_F1_class_0: 0.9302
• eval_F1_class_1: 0.0
• eval_F1_class_2: 0.8950
• eval_F1_class_3: 0.8000
• eval_F1_class_4: 0.8000
• eval_F1_class_5: 0.9057
• eval_F1_class_6: 0.7170
• eval_F1_class_7: 0.9663
• eval_F1_class_8: 0.9831
• eval_F1_class_9: 0.7931
• eval_F1_class_10: 0.8483
• eval_F1_class_11: 0.8333
• eval_F1_class_12: 0.7975
• eval_F1_class_13: 0.5714
• eval_F1_class_14: 0.8734
• eval_F1_class_15: 0.3077
• eval_F1_class_16: 0.0
• eval_F1_class_17: 0.9760
• eval_F1_class_18: 0.8525
• eval_F1_class_19: 0.9231
• eval_runtime: 34.849
• eval_samples_per_second: 32.426
• eval_steps_per_second: 2.037
• epoch: 3.93
• step: 2500

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: 5

Framework versions

• Transformers 4.32.0
• Pytorch 2.0.1+cu117
• Datasets 2.14.4
• Tokenizers 0.13.3