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bert_base_cased_MultiClass_v2 – AI Model by Ojeda01 | AlphaNeural AI
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Ojeda01
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bert_base_cased_MultiClass_v2
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
autotrain_compatible
endpoints_compatible
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bert_base_cased_MultiClass_v2
This model is a fine-tuned version of
HMEXBI/bert_base_cased_MultiClass
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.9806
Accuracy: 0.8101
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: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.1396
1.0
545
0.9023
0.7615
0.6961
2.0
1090
0.8074
0.7798
0.492
3.0
1635
0.8216
0.8009
0.3032
4.0
2180
0.9264
0.8018
0.1898
5.0
2725
0.9806
0.8101
Framework versions
Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.0
Tokenizers 0.13.2
