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results – AI Model by karunesh234 | 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
text-embeddings-inference
endpoints_compatible
us
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Model card
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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: 0.5096
Accuracy: 0.848
F1: 0.8468
Precision: 0.84
Recall: 0.8537
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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.45
1.0
250
0.4892
0.816
0.8375
0.7406
0.9634
0.253
2.0
500
0.5096
0.848
0.8468
0.84
0.8537
Framework versions
Transformers 4.44.2
Pytorch 2.10.0+cu128
Datasets 2.19.0
Tokenizers 0.19.1
