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distilbert-finetuned-ner – AI Model by JinOhara | AlphaNeural AI
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distilbert-finetuned-ner
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transformers
tensorboard
safetensors
distilbert
token-classification
generated_from_trainer
conll2003
distilbert/distilbert-base-uncased
finetune
apache-2.0
model-index
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: 0.0634
Precision: 0.9267
Recall: 0.9358
F1: 0.9312
Accuracy: 0.9832
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.2505
1.0
878
0.0693
0.9063
0.9224
0.9143
0.9802
0.0525
2.0
1756
0.0616
0.9206
0.9331
0.9268
0.9828
0.0296
3.0
2634
0.0634
0.9267
0.9358
0.9312
0.9832
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.1
Tokenizers 0.21.1
