readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_4_ternary
    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_4_ternary
  
  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: 1.2981
  - F1: 0.7565
  
  ## 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   | 289  | 0.5588          | 0.6984 |
  | 0.5547        | 2.0   | 578  | 0.5283          | 0.7336 |
  | 0.5547        | 3.0   | 867  | 0.7038          | 0.7202 |
  | 0.2479        | 4.0   | 1156 | 0.8949          | 0.7284 |
  | 0.2479        | 5.0   | 1445 | 0.9959          | 0.7286 |
  | 0.1181        | 6.0   | 1734 | 1.0663          | 0.7311 |
  | 0.0508        | 7.0   | 2023 | 1.2377          | 0.7054 |
  | 0.0508        | 8.0   | 2312 | 1.2981          | 0.7565 |
  | 0.0185        | 9.0   | 2601 | 1.3532          | 0.7407 |
  | 0.0185        | 10.0  | 2890 | 1.5365          | 0.7333 |
  | 0.0103        | 11.0  | 3179 | 1.5184          | 0.7423 |
  | 0.0103        | 12.0  | 3468 | 1.6009          | 0.7420 |
  | 0.0123        | 13.0  | 3757 | 1.6395          | 0.7402 |
  | 0.008         | 14.0  | 4046 | 1.6838          | 0.7429 |
  | 0.008         | 15.0  | 4335 | 1.6176          | 0.7490 |
  | 0.0012        | 16.0  | 4624 | 1.7873          | 0.7345 |
  | 0.0012        | 17.0  | 4913 | 1.6761          | 0.7412 |
  | 0.0044        | 18.0  | 5202 | 1.7356          | 0.7417 |
  | 0.0044        | 19.0  | 5491 | 1.7686          | 0.7502 |
  | 0.0045        | 20.0  | 5780 | 1.7668          | 0.7406 |
  | 0.0017        | 21.0  | 6069 | 1.8411          | 0.7381 |
  | 0.0017        | 22.0  | 6358 | 1.8147          | 0.7469 |
  | 0.0012        | 23.0  | 6647 | 1.8028          | 0.7489 |
  | 0.0012        | 24.0  | 6936 | 1.8147          | 0.7453 |
  | 0.0026        | 25.0  | 7225 | 1.8257          | 0.7475 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  