readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_2_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_2_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: 1.5810
  - F1: 0.7620
  
  ## 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   | 294  | 0.5886          | 0.7239 |
  | 0.557         | 2.0   | 588  | 0.5085          | 0.7524 |
  | 0.557         | 3.0   | 882  | 0.6332          | 0.7530 |
  | 0.2456        | 4.0   | 1176 | 0.8749          | 0.7161 |
  | 0.2456        | 5.0   | 1470 | 1.0601          | 0.7371 |
  | 0.1112        | 6.0   | 1764 | 1.1885          | 0.7451 |
  | 0.0484        | 7.0   | 2058 | 1.3027          | 0.7240 |
  | 0.0484        | 8.0   | 2352 | 1.4647          | 0.7259 |
  | 0.0259        | 9.0   | 2646 | 1.4476          | 0.7322 |
  | 0.0259        | 10.0  | 2940 | 1.4826          | 0.7388 |
  | 0.0164        | 11.0  | 3234 | 1.5869          | 0.7333 |
  | 0.0109        | 12.0  | 3528 | 1.5954          | 0.7539 |
  | 0.0109        | 13.0  | 3822 | 1.5810          | 0.7620 |
  | 0.0082        | 14.0  | 4116 | 1.7165          | 0.7335 |
  | 0.0082        | 15.0  | 4410 | 1.8152          | 0.7414 |
  | 0.004         | 16.0  | 4704 | 1.7411          | 0.7474 |
  | 0.004         | 17.0  | 4998 | 1.8692          | 0.7355 |
  | 0.0034        | 18.0  | 5292 | 1.8727          | 0.7303 |
  | 0.0009        | 19.0  | 5586 | 1.9813          | 0.7305 |
  | 0.0009        | 20.0  | 5880 | 1.9764          | 0.7391 |
  | 0.0012        | 21.0  | 6174 | 2.0170          | 0.7291 |
  | 0.0012        | 22.0  | 6468 | 2.0240          | 0.7391 |
  | 0.0004        | 23.0  | 6762 | 2.0311          | 0.7352 |
  | 0.0014        | 24.0  | 7056 | 2.0174          | 0.7334 |
  | 0.0014        | 25.0  | 7350 | 2.0282          | 0.7381 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  