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nathanReitinger/scotusPRED

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README.md CHANGED
@@ -1,22 +1,26 @@
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  ---
 
 
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  tags:
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- - generated_from_keras_callback
 
 
 
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  model-index:
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- - name: nathanReitinger/scotusPRED
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  results: []
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  ---
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- <!-- This model card has been generated automatically according to the information Keras had access to. You should
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- probably proofread and complete it, then remove this comment. -->
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- # nathanReitinger/scotusPRED
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- This model is a fine-tuned version of [pile-of-law/legalbert-large-1.7M-2](https://huggingface.co/pile-of-law/legalbert-large-1.7M-2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.6960
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- - Validation Loss: 0.6932
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- - Train Accuracy: 0.4809
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- - Epoch: 1
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  ## Model description
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@@ -35,20 +39,28 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 72, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
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- - training_precision: float32
 
 
 
 
 
 
 
 
 
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  ### Training results
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- | Train Loss | Validation Loss | Train Accuracy | Epoch |
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- |:----------:|:---------------:|:--------------:|:-----:|
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- | 0.7225 | 0.6917 | 0.5191 | 0 |
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- | 0.6960 | 0.6932 | 0.4809 | 1 |
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  ### Framework versions
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- - Transformers 4.30.2
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- - TensorFlow 2.11.0
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- - Datasets 2.13.2
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- - Tokenizers 0.13.3
 
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  ---
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+ license: apache-2.0
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+ base_model: allenai/longformer-base-4096
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  tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - f1
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  model-index:
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+ - name: scotusPRED
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  results: []
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  ---
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+ # scotusPRED
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+ This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6335
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+ - Accuracy: 0.6735
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+ - F1: 0.0
 
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 200
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+ - num_epochs: 1
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+ - mixed_precision_training: Native AMP
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|
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+ | 0.6824 | 1.0 | 195 | 0.6335 | 0.6735 | 0.0 |
 
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  ### Framework versions
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+ - Transformers 4.39.3
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+ - Pytorch 2.2.2+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
config.json CHANGED
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  {
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- "_name_or_path": "pile-of-law/legalbert-large-1.7M-2",
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  }
 
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+ "problem_type": "single_label_classification",
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  }
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