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ner-results-3 – AI Model by datmieu2k4 | AlphaNeural AI
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ner-results-3
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transformers
safetensors
roberta
token-classification
bert-ner-address
generated_from_trainer
FacebookAI/roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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ner-results-3
This model is a fine-tuned version of
roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0132
Precision: 0.9940
Recall: 0.9950
F1: 0.9945
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: 32
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
0.0176
1.0
71551
0.0148
0.9932
0.9953
0.9943
0.008
2.0
143102
0.0108
0.9950
0.9958
0.9954
Framework versions
Transformers 4.51.1
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0
