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unli – AI Model by JacobQuintero | AlphaNeural AI
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JacobQuintero
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unli
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Model card
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unli
This model is a fine-tuned version of
bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0752
Accuracy: 0.9681
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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.0808
1.0
1735
0.0737
0.9681
0.0626
2.0
3470
0.0765
0.9681
0.0453
3.0
5205
0.0752
0.9681
Framework versions
Transformers 4.20.1
Pytorch 1.12.1
Datasets 2.10.1
Tokenizers 0.12.1
