readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-small-finetuned-ner-to-multilabel-xglue-ner-new
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # bert-small-finetuned-ner-to-multilabel-xglue-ner-new
  
  This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0525
  
  ## 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: 3e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: constant
  - num_epochs: 40
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 0.1842        | 0.28  | 500  | 0.0937          |
  | 0.0858        | 0.57  | 1000 | 0.0666          |
  | 0.07          | 0.85  | 1500 | 0.0586          |
  | 0.0535        | 1.14  | 2000 | 0.0482          |
  | 0.0413        | 1.42  | 2500 | 0.0541          |
  | 0.0445        | 1.71  | 3000 | 0.0451          |
  | 0.0378        | 1.99  | 3500 | 0.0531          |
  | 0.0248        | 2.28  | 4000 | 0.0501          |
  | 0.0255        | 2.56  | 4500 | 0.0525          |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  