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bert_hierarchical_ecthr_a – AI Model by dawningz | AlphaNeural AI
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bert_hierarchical_ecthr_a
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transformers
safetensors
generated_from_trainer
nlpaueb/legal-bert-base-uncased
finetune
cc-by-sa-4.0
endpoints_compatible
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bert_hierarchical_ecthr_a
This model is a fine-tuned version of
nlpaueb/legal-bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1302
F1 Micro: 0.7626
F1 Macro: 0.7067
Accuracy: 0.6
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: 3e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3.0
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
F1 Micro
F1 Macro
Accuracy
0.1161
1.0
1125
0.1649
0.7053
0.5563
0.533
0.1055
2.0
2250
0.1340
0.7565
0.6584
0.598
0.1045
3.0
3375
0.1302
0.7626
0.7067
0.6
Framework versions
Transformers 4.57.3
Pytorch 2.8.0+cu126
Datasets 4.4.1
Tokenizers 0.22.1
