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ag_news-Classification – AI Model by shed-e | AlphaNeural AI
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shed-e
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ag_news-Classification
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transformers
pytorch
bert
text-classification
generated_from_trainer
ag_news
mit
model-index
autotrain_compatible
endpoints_compatible
us
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Model card
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results
This model is a fine-tuned version of
prajjwal1/bert-tiny
on the ag_news dataset. It achieves the following results on the evaluation set:
Loss: 0.3320
Accuracy: 0.8951
F1: 0.8964
Precision: 0.8978
Recall: 0.8965
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: 0.0003
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.2783
1.0
625
0.3046
0.8949
0.8960
0.8970
0.8963
0.1878
2.0
1250
0.3139
0.8954
0.8971
0.8995
0.8965
0.1311
3.0
1875
0.3320
0.8951
0.8964
0.8978
0.8965
Framework versions
Transformers 4.22.0
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1
