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distilbert-base-uncased-finetuned-ner – AI Model by Kishansai | AlphaNeural AI
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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
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 None dataset. It achieves the following results on the evaluation set:
Loss: 0.1879
Precision: 0.7745
Recall: 0.8033
F1: 0.7886
Accuracy: 0.9471
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_FUSED 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
No log
1.0
176
0.2152
0.7380
0.7978
0.7667
0.9423
No log
2.0
352
0.1918
0.7847
0.7682
0.7763
0.9444
0.2385
3.0
528
0.1879
0.7745
0.8033
0.7886
0.9471
Framework versions
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
