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deberta-v3-large-finetuned-synthetic-multi-class – AI Model by domenicrosati | AlphaNeural AI
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deberta-v3-large-finetuned-synthetic-multi-class
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transformers
pytorch
tensorboard
deberta-v2
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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deberta-v3-large-finetuned-synthetic-multi-class
This model is a fine-tuned version of
microsoft/deberta-v3-large
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0223
F1: 0.9961
Precision: 0.9961
Recall: 0.9961
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: 6e-06
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
F1
Precision
Recall
0.0278
1.0
10953
0.0352
0.9936
0.9935
0.9936
0.0143
2.0
21906
0.0252
0.9952
0.9952
0.9953
0.0014
3.0
32859
0.0267
0.9955
0.9955
0.9955
Framework versions
Transformers 4.18.0
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1
