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ner_trainer – AI Model by jenniferjane | AlphaNeural AI
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ner_trainer
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transformers
pytorch
tensorboard
distilbert
token-classification
generated_from_trainer
conll2003
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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ner_trainer
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: 0.1069
Precision: 0.9231
Recall: 0.9325
F1: 0.9278
Accuracy: 0.9830
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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0029
1.0
1756
0.1069
0.9231
0.9325
0.9278
0.9830
Framework versions
Transformers 4.21.3
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1
