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distilbert-base-uncased-finetuned-ner – AI Model by Senthilkumar-M | AlphaNeural AI
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Senthilkumar-M
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distilbert-base-uncased-finetuned-ner
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transformers
tensorboard
safetensors
distilbert
token-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
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 an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0599
Precision: 0.9291
Recall: 0.9376
F1: 0.9333
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
0.2446
1.0
878
0.0702
0.9038
0.9207
0.9122
0.9798
0.0499
2.0
1756
0.0606
0.9248
0.9313
0.9280
0.9830
0.0303
3.0
2634
0.0599
0.9291
0.9376
0.9333
0.9842
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.2
