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deberta-v3-base-orgs-v3 – AI Model by nbroad | AlphaNeural AI
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deberta-v3-base-orgs-v3
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transformers
safetensors
deberta-v2
token-classification
generated_from_trainer
microsoft/deberta-v3-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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deberta-v3-base-orgs-v3
This model is a fine-tuned version of
microsoft/deberta-v3-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1182
Precision: 0.8008
Recall: 0.7751
F1: 0.7877
Accuracy: 0.9627
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: 8e-05
train_batch_size: 256
eval_batch_size: 256
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 20
num_epochs: 3.0
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0526
1.4
600
0.1109
0.7917
0.7741
0.7828
0.9621
0.0434
2.8
1200
0.1182
0.8008
0.7751
0.7877
0.9627
Framework versions
Transformers 4.35.2
Pytorch 2.1.0a0+32f93b1
Datasets 2.15.0
Tokenizers 0.15.0
