readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased__subj__train-8-5
    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__subj__train-8-5
  
  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: 0.6927
  - Accuracy: 0.506
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.7102        | 1.0   | 3    | 0.6790          | 0.75     |
  | 0.6693        | 2.0   | 6    | 0.6831          | 0.75     |
  | 0.6438        | 3.0   | 9    | 0.6876          | 0.75     |
  | 0.6047        | 4.0   | 12   | 0.6970          | 0.75     |
  | 0.547         | 5.0   | 15   | 0.7065          | 0.75     |
  | 0.4885        | 6.0   | 18   | 0.7114          | 0.75     |
  | 0.4601        | 7.0   | 21   | 0.7147          | 0.5      |
  | 0.4017        | 8.0   | 24   | 0.7178          | 0.5      |
  | 0.3474        | 9.0   | 27   | 0.7145          | 0.5      |
  | 0.2624        | 10.0  | 30   | 0.7153          | 0.5      |
  | 0.2175        | 11.0  | 33   | 0.7158          | 0.5      |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2
  - Tokenizers 0.10.3
  