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our_awesome_BERT_model – AI Model by PetyaPetrova | AlphaNeural AI
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our_awesome_BERT_model
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transformers
tensorboard
safetensors
distilbert
token-classification
generated_from_trainer
distilbert/distilbert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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our_awesome_BERT_model
This model is a fine-tuned version of
distilbert/distilbert-base-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0567
Precision: 0.7594
Recall: 0.7909
F1: 0.7748
Accuracy: 0.9825
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.1072
1.0
784
0.0602
0.7686
0.7360
0.7520
0.9807
0.0271
2.0
1568
0.0567
0.7594
0.7909
0.7748
0.9825
Framework versions
Transformers 4.39.3
Pytorch 2.2.0+cpu
Datasets 2.19.0
Tokenizers 0.15.2
