readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: job-listing-relevance-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-relevance-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: 0.1649
  
  ## 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 0.7435        | 0.43  | 50   | 0.6889          |
  | 0.3222        | 0.87  | 100  | 0.2906          |
  | 0.2573        | 1.3   | 150  | 0.1937          |
  | 0.1205        | 1.74  | 200  | 0.1411          |
  | 0.1586        | 2.17  | 250  | 0.2008          |
  | 0.0755        | 2.61  | 300  | 0.1926          |
  | 0.062         | 3.04  | 350  | 0.2257          |
  | 0.0644        | 3.48  | 400  | 0.1497          |
  | 0.1034        | 3.91  | 450  | 0.1561          |
  | 0.008         | 4.35  | 500  | 0.2067          |
  | 0.0616        | 4.78  | 550  | 0.2067          |
  | 0.0766        | 5.22  | 600  | 0.1494          |
  | 0.0029        | 5.65  | 650  | 0.2078          |
  | 0.1076        | 6.09  | 700  | 0.1669          |
  | 0.0025        | 6.52  | 750  | 0.1564          |
  | 0.0498        | 6.95  | 800  | 0.2355          |
  | 0.0011        | 7.39  | 850  | 0.1652          |
  | 0.0271        | 7.82  | 900  | 0.1731          |
  | 0.012         | 8.26  | 950  | 0.1590          |
  | 0.0257        | 8.69  | 1000 | 0.1638          |
  | 0.0009        | 9.13  | 1050 | 0.1851          |
  | 0.0013        | 9.56  | 1100 | 0.1613          |
  | 0.0015        | 10.0  | 1150 | 0.1649          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  