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bert-base-uncased-fine-tuned – AI Model by Lecs | AlphaNeural AI
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Lecs
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bert-base-uncased-fine-tuned
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transformers
pytorch
tensorboard
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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bert-base-uncased-fine-tuned
This model is a fine-tuned version of
bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4464
Accuracy: 0.8444
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: 32
eval_batch_size: 32
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
No log
1.0
141
0.5832
0.8107
No log
2.0
282
0.4464
0.8444
Framework versions
Transformers 4.33.1
Pytorch 2.0.1+cpu
Datasets 2.14.5
Tokenizers 0.13.3
