readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: job-listing-filtering-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. -->
  
  # job-listing-filtering-model
  
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1992
  
  ## 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
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 25
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 0.4639        | 1.55  | 50   | 0.4343          |
  | 0.407         | 3.12  | 100  | 0.3589          |
  | 0.3459        | 4.68  | 150  | 0.3110          |
  | 0.2871        | 6.25  | 200  | 0.2604          |
  | 0.1966        | 7.8   | 250  | 0.2004          |
  | 0.0994        | 9.37  | 300  | 0.1766          |
  | 0.0961        | 10.92 | 350  | 0.2007          |
  | 0.0954        | 12.49 | 400  | 0.1716          |
  | 0.0498        | 14.06 | 450  | 0.1642          |
  | 0.0419        | 15.62 | 500  | 0.1811          |
  | 0.0232        | 17.18 | 550  | 0.1872          |
  | 0.0146        | 18.74 | 600  | 0.1789          |
  | 0.0356        | 20.31 | 650  | 0.1984          |
  | 0.0325        | 21.86 | 700  | 0.1845          |
  | 0.0381        | 23.43 | 750  | 0.1994          |
  | 0.0063        | 24.98 | 800  | 0.1992          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  