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BERTClassificationBaseline – AI Model by Gillner | AlphaNeural AI
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Gillner
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BERTClassificationBaseline
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transformers
pytorch
bert
text-classification
generated_from_trainer
autotrain_compatible
endpoints_compatible
us
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BERTClassificationBaseline
This model is a fine-tuned version of
allenai/scibert_scivocab_uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.2709
Accuracy: 0.4
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-06
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
157
1.3100
0.4286
No log
2.0
314
1.2709
0.4
Framework versions
Transformers 4.22.1
Pytorch 1.12.1
Datasets 2.5.2
Tokenizers 0.11.0
