readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: sumups-batch4-model
    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. -->
  
  # sumups-batch4-model
  
  This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2992
  - Precision: 0.0073
  - Recall: 0.0337
  - F1: 0.0119
  - Accuracy: 0.4875
  
  ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 20   | 1.5243          | 0.0035    | 0.0119 | 0.0054 | 0.4106   |
  | No log        | 2.0   | 40   | 1.3877          | 0.0039    | 0.0119 | 0.0058 | 0.4421   |
  | No log        | 3.0   | 60   | 1.3144          | 0.0073    | 0.0238 | 0.0112 | 0.4723   |
  | No log        | 4.0   | 80   | 1.2957          | 0.0079    | 0.0356 | 0.0129 | 0.4877   |
  | No log        | 5.0   | 100  | 1.2992          | 0.0073    | 0.0337 | 0.0119 | 0.4875   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  