readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_6_binary
    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_6_binary
  
  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: 1.6838
  - F1: 0.7881
  
  ## 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  | 0.4181          | 0.7732 |
  | 0.4097        | 2.0   | 580  | 0.3967          | 0.7697 |
  | 0.4097        | 3.0   | 870  | 0.5811          | 0.7797 |
  | 0.2034        | 4.0   | 1160 | 0.8684          | 0.7320 |
  | 0.2034        | 5.0   | 1450 | 0.9116          | 0.7718 |
  | 0.0794        | 6.0   | 1740 | 1.0588          | 0.7690 |
  | 0.0278        | 7.0   | 2030 | 1.2092          | 0.7738 |
  | 0.0278        | 8.0   | 2320 | 1.2180          | 0.7685 |
  | 0.0233        | 9.0   | 2610 | 1.3005          | 0.7676 |
  | 0.0233        | 10.0  | 2900 | 1.4009          | 0.7634 |
  | 0.0093        | 11.0  | 3190 | 1.4528          | 0.7805 |
  | 0.0093        | 12.0  | 3480 | 1.4803          | 0.7859 |
  | 0.0088        | 13.0  | 3770 | 1.4775          | 0.7750 |
  | 0.0077        | 14.0  | 4060 | 1.6171          | 0.7699 |
  | 0.0077        | 15.0  | 4350 | 1.6429          | 0.7636 |
  | 0.0047        | 16.0  | 4640 | 1.5619          | 0.7819 |
  | 0.0047        | 17.0  | 4930 | 1.5833          | 0.7724 |
  | 0.0034        | 18.0  | 5220 | 1.6400          | 0.7853 |
  | 0.0008        | 19.0  | 5510 | 1.6508          | 0.7792 |
  | 0.0008        | 20.0  | 5800 | 1.6838          | 0.7881 |
  | 0.0009        | 21.0  | 6090 | 1.6339          | 0.7829 |
  | 0.0009        | 22.0  | 6380 | 1.6824          | 0.7806 |
  | 0.0016        | 23.0  | 6670 | 1.6867          | 0.7876 |
  | 0.0016        | 24.0  | 6960 | 1.7107          | 0.7877 |
  | 0.0013        | 25.0  | 7250 | 1.6933          | 0.7812 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  