readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_2_binary_v1
    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. -->
  
  # distilbert-base-uncased_fold_2_binary_v1
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8833
  - F1: 0.7841
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - 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 | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.0   | 290  | 0.4060          | 0.8070 |
  | 0.3981        | 2.0   | 580  | 0.4534          | 0.8072 |
  | 0.3981        | 3.0   | 870  | 0.5460          | 0.7961 |
  | 0.1985        | 4.0   | 1160 | 0.8684          | 0.7818 |
  | 0.1985        | 5.0   | 1450 | 0.9009          | 0.7873 |
  | 0.0844        | 6.0   | 1740 | 1.1529          | 0.7825 |
  | 0.0329        | 7.0   | 2030 | 1.3185          | 0.7850 |
  | 0.0329        | 8.0   | 2320 | 1.4110          | 0.7862 |
  | 0.0109        | 9.0   | 2610 | 1.4751          | 0.7784 |
  | 0.0109        | 10.0  | 2900 | 1.6276          | 0.7723 |
  | 0.0071        | 11.0  | 3190 | 1.6779          | 0.7861 |
  | 0.0071        | 12.0  | 3480 | 1.6258          | 0.7850 |
  | 0.0041        | 13.0  | 3770 | 1.6324          | 0.7903 |
  | 0.0109        | 14.0  | 4060 | 1.7563          | 0.7932 |
  | 0.0109        | 15.0  | 4350 | 1.6740          | 0.7906 |
  | 0.0079        | 16.0  | 4640 | 1.7468          | 0.7944 |
  | 0.0079        | 17.0  | 4930 | 1.7095          | 0.7879 |
  | 0.0067        | 18.0  | 5220 | 1.7293          | 0.7912 |
  | 0.0021        | 19.0  | 5510 | 1.7875          | 0.7848 |
  | 0.0021        | 20.0  | 5800 | 1.7462          | 0.7906 |
  | 0.0026        | 21.0  | 6090 | 1.8549          | 0.7815 |
  | 0.0026        | 22.0  | 6380 | 1.8314          | 0.7860 |
  | 0.0021        | 23.0  | 6670 | 1.8577          | 0.7839 |
  | 0.0021        | 24.0  | 6960 | 1.8548          | 0.7883 |
  | 0.0001        | 25.0  | 7250 | 1.8833          | 0.7841 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  