readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_8_ternary_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_8_ternary_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: 1.8474
  - F1: 0.8022
  
  ## 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  | 0.5398          | 0.7838 |
  | 0.5509        | 2.0   | 578  | 0.6062          | 0.7703 |
  | 0.5509        | 3.0   | 867  | 0.6563          | 0.7666 |
  | 0.2366        | 4.0   | 1156 | 0.7688          | 0.7961 |
  | 0.2366        | 5.0   | 1445 | 1.0968          | 0.7690 |
  | 0.1247        | 6.0   | 1734 | 1.1414          | 0.7924 |
  | 0.0482        | 7.0   | 2023 | 1.2159          | 0.7875 |
  | 0.0482        | 8.0   | 2312 | 1.2703          | 0.7887 |
  | 0.0245        | 9.0   | 2601 | 1.3401          | 0.7985 |
  | 0.0245        | 10.0  | 2890 | 1.4645          | 0.7961 |
  | 0.0149        | 11.0  | 3179 | 1.5632          | 0.7801 |
  | 0.0149        | 12.0  | 3468 | 1.5249          | 0.7875 |
  | 0.0124        | 13.0  | 3757 | 1.6263          | 0.7948 |
  | 0.0038        | 14.0  | 4046 | 1.8059          | 0.7764 |
  | 0.0038        | 15.0  | 4335 | 1.7649          | 0.7776 |
  | 0.0061        | 16.0  | 4624 | 1.8293          | 0.7850 |
  | 0.0061        | 17.0  | 4913 | 1.8316          | 0.7887 |
  | 0.0022        | 18.0  | 5202 | 1.7628          | 0.7973 |
  | 0.0022        | 19.0  | 5491 | 1.8763          | 0.7862 |
  | 0.002         | 20.0  | 5780 | 1.8409          | 0.7899 |
  | 0.0026        | 21.0  | 6069 | 1.8146          | 0.8022 |
  | 0.0026        | 22.0  | 6358 | 1.8420          | 0.7973 |
  | 0.0008        | 23.0  | 6647 | 1.8683          | 0.8010 |
  | 0.0008        | 24.0  | 6936 | 1.8571          | 0.8010 |
  | 0.0015        | 25.0  | 7225 | 1.8474          | 0.8022 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  