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arxiv_scibert_classifier – AI Model by GogiGigantic | AlphaNeural AI
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arxiv_scibert_classifier
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tensorboard
safetensors
bert
generated_from_trainer
allenai/scibert_scivocab_uncased
finetune
us
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arxiv_scibert_classifier
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: 0.6849
Accuracy: 0.8301
F1 Macro: 0.8300
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-05
train_batch_size: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1 Macro
0.4732
1.0
3750
0.5591
0.8233
0.8235
0.3428
2.0
7500
0.5882
0.8225
0.8231
0.1935
3.0
11250
0.6849
0.8301
0.8300
Framework versions
Transformers 4.41.2
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.19.1
