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news_to_return_july_31 – AI Model by LangyaTech | AlphaNeural AI
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LangyaTech
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news_to_return_july_31
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Model card
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news_to_return_july_31
This model is a fine-tuned version of
google-bert/bert-base-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.1593
Accuracy: 0.5256
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: 16
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
No log
1.0
115
0.9817
0.5256
No log
2.0
230
1.0072
0.5349
No log
3.0
345
1.0330
0.5256
No log
4.0
460
1.1182
0.5267
0.7588
5.0
575
1.1593
0.5256
Framework versions
Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
