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bert_ftbasic_ner_model – AI Model by yumcoco | AlphaNeural AI
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bert_ftbasic_ner_model
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transformers
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
autotrain_compatible
endpoints_compatible
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bert_ftbasic_ner_model
This model is a fine-tuned version of
bert-base-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1751
Precision: 0.6008
Recall: 0.6575
F1: 0.6279
Accuracy: 0.9559
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: 8
eval_batch_size: 8
seed: 42
optimizer: Use 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
No log
1.0
249
0.2199
0.4997
0.6192
0.5531
0.9400
No log
2.0
498
0.2170
0.5711
0.6162
0.5928
0.9456
0.1993
3.0
747
0.2313
0.5415
0.6586
0.5943
0.9430
Framework versions
Transformers 4.46.1
Pytorch 2.5.1+cu118
Datasets 3.1.0
Tokenizers 0.20.1
