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deberta-v3-small-legal – AI Model by maticzav | AlphaNeural AI
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deberta-v3-small-legal
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transformers
safetensors
deberta-v2
text-classification
generated_from_trainer
microsoft/deberta-v3-small
finetune
mit
text-embeddings-inference
endpoints_compatible
us
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deberta-v3-small-legal
This model is a fine-tuned version of
microsoft/deberta-v3-small
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1942
Accuracy: 0.9461
F1: 0.8539
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: 2.8370838248924945e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
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: 0.06391779741439595
num_epochs: 4
Training results
Framework versions
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
