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deberta-v3-large-dapt-scientific-papers-pubmed-tapt – AI Model by domenicrosati | AlphaNeural AI
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deberta-v3-large-dapt-scientific-papers-pubmed-tapt
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transformers
pytorch
tensorboard
deberta-v2
fill-mask
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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deberta-v3-large-dapt-scientific-papers-pubmed-tapt
This model is a fine-tuned version of
domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed
on the None dataset. It achieves the following results on the evaluation set:
Loss: 2.4429
Accuracy: 0.5915
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: 5e-05
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
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
3.3855
1.0
4134
3.2334
0.4953
2.9224
2.0
8268
2.8317
0.5430
2.703
3.0
12402
2.6141
0.5665
2.4963
4.0
16536
2.4918
0.5855
2.399
5.0
20670
2.4429
0.5915
Framework versions
Transformers 4.18.0
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1
