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my_ner_model – AI Model by nkimsjoyce | AlphaNeural AI
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my_ner_model
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transformers
safetensors
distilbert
token-classification
generated_from_trainer
wnut_17
distilbert/distilbert-base-uncased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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my_ner_model
This model is a fine-tuned version of
distilbert-base-uncased
on the wnut_17 dataset. It achieves the following results on the evaluation set:
Loss: 0.2689
Precision: 0.6021
Recall: 0.3253
F1: 0.4224
Accuracy: 0.9422
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
213
0.2767
0.5847
0.2623
0.3621
0.9394
No log
2.0
426
0.2689
0.6021
0.3253
0.4224
0.9422
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
