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bert-finetuned-ner – AI Model by hanwen1232 | AlphaNeural AI
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hanwen1232
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bert-finetuned-ner
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transformers
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-finetuned-ner
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: 0.1749
Precision: 0.5782
Recall: 0.6635
F1: 0.6179
Accuracy: 0.9548
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
0.2258
0.4744
0.6031
0.5311
0.9355
No log
2.0
498
0.2214
0.5604
0.6170
0.5873
0.9446
0.2066
3.0
747
0.2324
0.5223
0.6499
0.5792
0.9414
Framework versions
Transformers 4.46.0
Pytorch 2.4.1+cpu
Datasets 3.0.2
Tokenizers 0.20.1
