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scotusPRED – AI Model by nathanReitinger | AlphaNeural AI
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scotusPRED
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transformers
tf
tensorboard
safetensors
longformer
text-classification
generated_from_trainer
allenai/longformer-base-4096
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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scotusPRED
This model is a fine-tuned version of
allenai/longformer-base-4096
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6335
Accuracy: 0.6735
F1: 0.0
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: 5e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.6824
1.0
195
0.6335
0.6735
0.0
Framework versions
Transformers 4.39.3
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.15.2
