Hugging Face's logo

almaghrabima
/
ner_column_bert-base-NER

Token Classification
Transformers
PyTorch
English
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
ner_column_bert-base-NER / README.md
almaghrabima's picture
almaghrabima
Model save
86f4cc1
preview code
|
raw
history blame
3.31 kB
metadata
license: mit
base_model: dslim/bert-base-NER
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: ner_column_bert-base-NER
    results: []

ner_column_bert-base-NER

This model is a fine-tuned version of dslim/bert-base-NER on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1855
  • Precision: 0.7651
  • Recall: 0.7786
  • F1: 0.7718
  • Accuracy: 0.9026

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 702 0.7382 0.2576 0.1887 0.2178 0.7127
0.9356 2.0 1404 0.4405 0.5139 0.4331 0.4700 0.8157
0.5445 3.0 2106 0.3608 0.5712 0.5143 0.5413 0.8404
0.5445 4.0 2808 0.3226 0.6188 0.5840 0.6009 0.8550
0.4316 5.0 3510 0.2757 0.6788 0.6569 0.6676 0.8728
0.3605 6.0 4212 0.2828 0.6584 0.6346 0.6463 0.8697
0.3605 7.0 4914 0.2456 0.7108 0.6926 0.7015 0.8820
0.3153 8.0 5616 0.2385 0.7055 0.6986 0.7021 0.8855
0.282 9.0 6318 0.2345 0.7044 0.6961 0.7002 0.8853
0.2587 10.0 7020 0.2313 0.7081 0.7049 0.7065 0.8862
0.2587 11.0 7722 0.2026 0.7734 0.7537 0.7634 0.8968
0.239 12.0 8424 0.1980 0.7651 0.7687 0.7669 0.8991
0.2241 13.0 9126 0.2091 0.7368 0.7423 0.7395 0.8936
0.2241 14.0 9828 0.1954 0.7693 0.7684 0.7689 0.8987
0.2124 15.0 10530 0.1916 0.7668 0.7749 0.7708 0.9008
0.2025 16.0 11232 0.1841 0.7699 0.7794 0.7746 0.9024
0.2025 17.0 11934 0.1938 0.7527 0.7626 0.7576 0.8992
0.193 18.0 12636 0.1849 0.7705 0.7841 0.7772 0.9040
0.1877 19.0 13338 0.1927 0.7510 0.7649 0.7579 0.9005
0.1821 20.0 14040 0.1855 0.7651 0.7786 0.7718 0.9026

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.13.3