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results – AI Model by Yermahin | AlphaNeural AI
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results
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transformers
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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results
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: 0.0605
Accuracy: 0.9892
Precision: 0.9858
Recall: 0.9329
F1: 0.9586
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: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.0017
1.0
558
0.0605
0.9892
0.9858
0.9329
0.9586
0.0002
2.0
1116
0.0750
0.9892
0.9790
0.9396
0.9589
0.0164
3.0
1674
0.0809
0.9874
0.9655
0.9396
0.9524
Framework versions
Transformers 4.48.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.2
