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topic_classification – AI Model by Prezily | AlphaNeural AI | AlphaNeural AI
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Prezily
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topic_classification
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transformers
safetensors
bert
text-classification
generated_from_trainer
yahoo_answers_topics
google-bert/bert-base-uncased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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topic_classification
This model is a fine-tuned version of
bert-base-uncased
on the yahoo_answers_topics dataset. It achieves the following results on the evaluation set:
Loss: 1.1769
Accuracy: 0.6518
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: 0.0001
train_batch_size: 64
eval_batch_size: 128
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
1.005
1.0
625
1.0478
0.6519
0.7717
2.0
1250
1.0482
0.6557
0.4566
3.0
1875
1.1769
0.6518
Framework versions
Transformers 4.36.2
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0
