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insertion-prop-015-correct-data – AI Model by adasgaleus | AlphaNeural AI
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insertion-prop-015-correct-data
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transformers
pytorch
tensorboard
distilbert
token-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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insertion-prop-015-correct-data
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0497
Precision: 0.8907
Recall: 0.8518
F1: 0.8708
Accuracy: 0.9816
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: 64
eval_batch_size: 64
seed: 42
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
Precision
Recall
F1
Accuracy
0.0978
0.32
500
0.0581
0.8730
0.8300
0.8509
0.9787
0.0633
0.64
1000
0.0515
0.8867
0.8447
0.8652
0.9807
0.0588
0.96
1500
0.0497
0.8907
0.8518
0.8708
0.9816
Framework versions
Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2
