judithrosell / VF_BERT_ST_1000

huggingface.co
Total runs: 4
24-hour runs: 0
7-day runs: 0
30-day runs: 2
Model's Last Updated: September 05 2024
token-classification

Introduction of VF_BERT_ST_1000

Model Details of VF_BERT_ST_1000

VF_BERT_ST_1000

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

  • Loss: 0.1765
  • Precision: 0.9705
  • Recall: 0.9755
  • F1: 0.9730
  • Accuracy: 0.9636
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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 259 0.1575 0.9595 0.9658 0.9626 0.9503
0.2118 2.0 518 0.1388 0.9660 0.9743 0.9701 0.9597
0.2118 3.0 777 0.1366 0.9688 0.9734 0.9711 0.9613
0.0546 4.0 1036 0.1488 0.9673 0.9726 0.9699 0.9603
0.0546 5.0 1295 0.1663 0.9675 0.9736 0.9705 0.9609
0.0251 6.0 1554 0.1673 0.9685 0.9750 0.9717 0.9628
0.0251 7.0 1813 0.1708 0.9707 0.9753 0.9730 0.9639
0.0133 8.0 2072 0.1707 0.9701 0.9742 0.9721 0.9631
0.0133 9.0 2331 0.1771 0.9703 0.9754 0.9728 0.9635
0.0094 10.0 2590 0.1765 0.9705 0.9755 0.9730 0.9636
Framework versions
  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1

Runs of judithrosell VF_BERT_ST_1000 on huggingface.co

4
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3-day runs
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7-day runs
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More Information About VF_BERT_ST_1000 huggingface.co Model

More VF_BERT_ST_1000 license Visit here:

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VF_BERT_ST_1000 huggingface.co

VF_BERT_ST_1000 huggingface.co is an AI model on huggingface.co that provides VF_BERT_ST_1000's model effect (), which can be used instantly with this judithrosell VF_BERT_ST_1000 model. huggingface.co supports a free trial of the VF_BERT_ST_1000 model, and also provides paid use of the VF_BERT_ST_1000. Support call VF_BERT_ST_1000 model through api, including Node.js, Python, http.

judithrosell VF_BERT_ST_1000 online free

VF_BERT_ST_1000 huggingface.co is an online trial and call api platform, which integrates VF_BERT_ST_1000's modeling effects, including api services, and provides a free online trial of VF_BERT_ST_1000, you can try VF_BERT_ST_1000 online for free by clicking the link below.

judithrosell VF_BERT_ST_1000 online free url in huggingface.co:

https://huggingface.co/judithrosell/VF_BERT_ST_1000

VF_BERT_ST_1000 install

VF_BERT_ST_1000 is an open source model from GitHub that offers a free installation service, and any user can find VF_BERT_ST_1000 on GitHub to install. At the same time, huggingface.co provides the effect of VF_BERT_ST_1000 install, users can directly use VF_BERT_ST_1000 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

VF_BERT_ST_1000 install url in huggingface.co:

https://huggingface.co/judithrosell/VF_BERT_ST_1000

Url of VF_BERT_ST_1000

Provider of VF_BERT_ST_1000 huggingface.co

judithrosell
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Updated:September 09 2024