readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_13_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_13_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: 1.7433
  - F1: 0.8138
  
  ## 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   | 291  | 0.4101          | 0.8087 |
  | 0.4128        | 2.0   | 582  | 0.4605          | 0.8197 |
  | 0.4128        | 3.0   | 873  | 0.5011          | 0.8130 |
  | 0.1997        | 4.0   | 1164 | 0.6882          | 0.8147 |
  | 0.1997        | 5.0   | 1455 | 0.9653          | 0.8092 |
  | 0.0913        | 6.0   | 1746 | 1.1020          | 0.8031 |
  | 0.0347        | 7.0   | 2037 | 1.2687          | 0.8050 |
  | 0.0347        | 8.0   | 2328 | 1.2383          | 0.8103 |
  | 0.0173        | 9.0   | 2619 | 1.3631          | 0.8066 |
  | 0.0173        | 10.0  | 2910 | 1.4282          | 0.8001 |
  | 0.0104        | 11.0  | 3201 | 1.4410          | 0.8179 |
  | 0.0104        | 12.0  | 3492 | 1.5318          | 0.8018 |
  | 0.0063        | 13.0  | 3783 | 1.5866          | 0.8018 |
  | 0.0043        | 14.0  | 4074 | 1.4987          | 0.8159 |
  | 0.0043        | 15.0  | 4365 | 1.6275          | 0.8181 |
  | 0.0048        | 16.0  | 4656 | 1.5811          | 0.8231 |
  | 0.0048        | 17.0  | 4947 | 1.6228          | 0.8182 |
  | 0.0048        | 18.0  | 5238 | 1.7235          | 0.8138 |
  | 0.0055        | 19.0  | 5529 | 1.7018          | 0.8066 |
  | 0.0055        | 20.0  | 5820 | 1.7340          | 0.8069 |
  | 0.0046        | 21.0  | 6111 | 1.7143          | 0.8156 |
  | 0.0046        | 22.0  | 6402 | 1.7367          | 0.8159 |
  | 0.0037        | 23.0  | 6693 | 1.7551          | 0.8151 |
  | 0.0037        | 24.0  | 6984 | 1.7479          | 0.8145 |
  | 0.0009        | 25.0  | 7275 | 1.7433          | 0.8138 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  