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microtest – AI Model by zwellington | AlphaNeural AI
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zwellington
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microtest
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transformers
pytorch
bert
text-classification
generated_from_trainer
azaheadhealth
google-bert/bert-base-uncased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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microtest
This model is a fine-tuned version of
bert-base-uncased
on the azaheadhealth dataset. It achieves the following results on the evaluation set:
Loss: 0.6111
Accuracy: 1.0
F1: 1.0
Precision: 1.0
Recall: 1.0
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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 2
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.5955
0.5
1
0.6676
0.5
0.5
0.5
0.5
0.633
1.0
2
0.6111
1.0
1.0
1.0
1.0
Framework versions
Transformers 4.31.0
Pytorch 2.2.0+cu121
Datasets 2.16.1
Tokenizers 0.13.2
