SCOTUS_AI_15 / README.md
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metadata
license: cc-by-sa-4.0
base_model: raminass/scotus-v10
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: SCOTUS_AI
    results: []

SCOTUS_AI

This model is a fine-tuned version of raminass/scotus-v10 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7680
  • Accuracy: 0.8341

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

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5767 1.0 1800 0.6222 0.8243
0.2965 2.0 3600 0.6352 0.8339
0.1832 3.0 5400 0.7201 0.8261
0.0991 4.0 7200 0.7398 0.8356
0.0616 5.0 9000 0.7680 0.8341

Justices

Justice Count
Thomas 571
Scalia 473
Breyer 443
Stevens 407
Ginsburg 390
Kennedy 326
Alito 286
Souter 230
Sotomayor 226
O'Connor 167
Kagan 145
Rehnquist 144
Roberts 123
Gorsuch 109
Kavanaugh 65

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0