readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  model-index:
  - name: bert-base-uncased-cv-position-classifier
    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-base-uncased-cv-position-classifier
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.6924
  - Accuracy: {'accuracy': 0.5780703216130645}
  - F1: {'f1': 0.5780703216130645}
  - Precision: {'precision': 0.5780703216130645}
  
  ## 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: 5e-05
  - train_batch_size: 16
  - eval_batch_size: 8
  - 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 | Accuracy                         | F1                         | Precision                         |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:--------------------------:|:---------------------------------:|
  | 2.0336        | 1.14  | 1000 | 1.8856          | {'accuracy': 0.5259123479420097} | {'f1': 0.5259123479420097} | {'precision': 0.5259123479420097} |
  | 1.5348        | 2.28  | 2000 | 1.6924          | {'accuracy': 0.5780703216130645} | {'f1': 0.5780703216130645} | {'precision': 0.5780703216130645} |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.8.1+cu111
  - Datasets 1.6.2
  - Tokenizers 0.12.1
  