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distilbert-base-uncased-finetuned-ner – AI Model by Hank | AlphaNeural AI
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Hank
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distilbert-base-uncased-finetuned-ner
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transformers
pytorch
tensorboard
distilbert
token-classification
generated_from_trainer
conll2003
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distilbert-base-uncased-finetuned-ner
This model is a fine-tuned version of
distilbert-base-uncased
on the conll2003 dataset. It achieves the following results on the evaluation set:
Loss: 0.0612
Precision: 0.9259
Recall: 0.9369
F1: 0.9314
Accuracy: 0.9839
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.243
1.0
878
0.0703
0.9134
0.9181
0.9158
0.9806
0.0515
2.0
1756
0.0609
0.9214
0.9343
0.9278
0.9832
0.0305
3.0
2634
0.0612
0.9259
0.9369
0.9314
0.9839
Framework versions
Transformers 4.9.1
Pytorch 1.9.0+cu102
Datasets 1.11.0
Tokenizers 0.10.3
