readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_1_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_1_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: 2.1145
  - F1: 0.7757
  
  ## 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   | 290  | 0.5580          | 0.7646 |
  | 0.555         | 2.0   | 580  | 0.5820          | 0.7670 |
  | 0.555         | 3.0   | 870  | 0.6683          | 0.7757 |
  | 0.2633        | 4.0   | 1160 | 0.9137          | 0.7844 |
  | 0.2633        | 5.0   | 1450 | 1.1367          | 0.7708 |
  | 0.1148        | 6.0   | 1740 | 1.2192          | 0.7757 |
  | 0.0456        | 7.0   | 2030 | 1.4035          | 0.7633 |
  | 0.0456        | 8.0   | 2320 | 1.5185          | 0.7658 |
  | 0.0226        | 9.0   | 2610 | 1.6126          | 0.7782 |
  | 0.0226        | 10.0  | 2900 | 1.7631          | 0.7658 |
  | 0.0061        | 11.0  | 3190 | 1.7279          | 0.7794 |
  | 0.0061        | 12.0  | 3480 | 1.8548          | 0.7584 |
  | 0.0076        | 13.0  | 3770 | 1.9052          | 0.7646 |
  | 0.0061        | 14.0  | 4060 | 1.9100          | 0.7757 |
  | 0.0061        | 15.0  | 4350 | 1.9280          | 0.7732 |
  | 0.0025        | 16.0  | 4640 | 1.9991          | 0.7745 |
  | 0.0025        | 17.0  | 4930 | 1.9960          | 0.7757 |
  | 0.0035        | 18.0  | 5220 | 2.0018          | 0.7708 |
  | 0.0015        | 19.0  | 5510 | 2.1099          | 0.7646 |
  | 0.0015        | 20.0  | 5800 | 2.1061          | 0.7695 |
  | 0.0022        | 21.0  | 6090 | 2.0941          | 0.7757 |
  | 0.0022        | 22.0  | 6380 | 2.0967          | 0.7794 |
  | 0.0005        | 23.0  | 6670 | 2.1133          | 0.7745 |
  | 0.0005        | 24.0  | 6960 | 2.1042          | 0.7782 |
  | 0.0021        | 25.0  | 7250 | 2.1145          | 0.7757 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  