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legalcase_outcome_model_v2 – AI Model by Othniel74 | AlphaNeural AI
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legalcase_outcome_model_v2
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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legalcase_outcome_model_v2
This model is a fine-tuned version of
distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.9549
Accuracy: 0.3519
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
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.737
1.0
224
1.9877
0.3531
1.7261
2.0
448
1.9332
0.2984
1.6879
3.0
672
1.9163
0.3391
1.6007
4.0
896
1.9080
0.3369
1.3704
5.0
1120
1.9549
0.3519
Framework versions
Transformers 4.44.2
Pytorch 2.4.0
Datasets 3.0.0
Tokenizers 0.19.1
