readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_1_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_1_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: 1.7296
  - F1: 0.8038
  
  ## 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   | 288  | 0.4152          | 0.7903 |
  | 0.3956        | 2.0   | 576  | 0.4037          | 0.8083 |
  | 0.3956        | 3.0   | 864  | 0.5601          | 0.7996 |
  | 0.181         | 4.0   | 1152 | 0.8571          | 0.8023 |
  | 0.181         | 5.0   | 1440 | 0.9704          | 0.7822 |
  | 0.0935        | 6.0   | 1728 | 0.9509          | 0.8074 |
  | 0.0418        | 7.0   | 2016 | 1.1813          | 0.7736 |
  | 0.0418        | 8.0   | 2304 | 1.2619          | 0.7859 |
  | 0.0134        | 9.0   | 2592 | 1.4275          | 0.7863 |
  | 0.0134        | 10.0  | 2880 | 1.4035          | 0.8019 |
  | 0.0127        | 11.0  | 3168 | 1.4903          | 0.7897 |
  | 0.0127        | 12.0  | 3456 | 1.5853          | 0.7919 |
  | 0.0061        | 13.0  | 3744 | 1.6628          | 0.7957 |
  | 0.0058        | 14.0  | 4032 | 1.5736          | 0.8060 |
  | 0.0058        | 15.0  | 4320 | 1.6226          | 0.7929 |
  | 0.0065        | 16.0  | 4608 | 1.6395          | 0.8010 |
  | 0.0065        | 17.0  | 4896 | 1.6556          | 0.7993 |
  | 0.002         | 18.0  | 5184 | 1.7075          | 0.8030 |
  | 0.002         | 19.0  | 5472 | 1.6925          | 0.7964 |
  | 0.0058        | 20.0  | 5760 | 1.6511          | 0.8030 |
  | 0.0013        | 21.0  | 6048 | 1.6135          | 0.8037 |
  | 0.0013        | 22.0  | 6336 | 1.6739          | 0.8028 |
  | 0.0001        | 23.0  | 6624 | 1.7014          | 0.8109 |
  | 0.0001        | 24.0  | 6912 | 1.7015          | 0.8045 |
  | 0.002         | 25.0  | 7200 | 1.7296          | 0.8038 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  