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distilbert-base-uncased-finetuned-ner – AI Model by jwu205 | AlphaNeural AI
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jwu205
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distilbert-base-uncased-finetuned-ner
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pytorch
distilbert
generated_from_trainer
conll2003
distilbert/distilbert-base-uncased
finetune
apache-2.0
model-index
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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: 0.0664
Precision: 0.9306
Recall: 0.9393
F1: 0.9349
Accuracy: 0.9842
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
0.0525
1.0
878
0.0671
0.9121
0.9308
0.9213
0.9820
0.0287
2.0
1756
0.0640
0.9281
0.9361
0.9321
0.9838
0.0169
3.0
2634
0.0664
0.9306
0.9393
0.9349
0.9842
Framework versions
Transformers 4.32.1
Pytorch 2.2.1+cpu
Datasets 2.21.0
Tokenizers 0.13.2
