emmabedna / langtok-bert_uncased

huggingface.co
Total runs: 8
24-hour runs: 1
7-day runs: 3
30-day runs: 5
Model's Last Updated: November 12 2025
token-classification

Introduction of langtok-bert_uncased

Model Details of langtok-bert_uncased

langtok-bert_uncased

This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0170
  • Precision: 0.9227
  • Recall: 0.9267
  • F1: 0.9247
  • Accuracy: 0.9952
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: 3
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.1943 1.0 854 0.0200 0.9041 0.8954 0.8997 0.9939
0.0162 2.0 1708 0.0168 0.9185 0.9210 0.9197 0.9950
0.0085 3.0 2562 0.0170 0.9227 0.9267 0.9247 0.9952
Framework versions
  • Transformers 4.44.2
  • Pytorch 2.7.1+cu126
  • Datasets 3.0.1
  • Tokenizers 0.19.1

Runs of emmabedna langtok-bert_uncased on huggingface.co

8
Total runs
1
24-hour runs
1
3-day runs
3
7-day runs
5
30-day runs

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

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https://huggingface.co/emmabedna/langtok-bert_uncased

langtok-bert_uncased install

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

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https://huggingface.co/emmabedna/langtok-bert_uncased

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Total runs: 5
Run Growth: 3
Growth Rate: 60.00%
Updated:January 25 2025