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distilbert-NER-finetuned-ner – AI Model by deepaksiloka | AlphaNeural AI
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deepaksiloka
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distilbert-NER-finetuned-ner
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transformers
tensorboard
safetensors
distilbert
token-classification
generated_from_trainer
dslim/distilbert-NER
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distilbert-NER-finetuned-ner
This model is a fine-tuned version of
dslim/distilbert-NER
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0111
Precision: 0.8892
Recall: 0.9189
F1: 0.9038
Accuracy: 0.9968
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
No log
1.0
270
0.0155
0.8292
0.8918
0.8594
0.9952
0.0286
2.0
540
0.0121
0.8695
0.9198
0.8939
0.9965
0.0286
3.0
810
0.0111
0.8892
0.9189
0.9038
0.9968
Framework versions
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1
