readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: convnext-base-224_finetuned_on_unlabelled_IA_with_snorkel_labels
    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. -->
  
  # convnext-base-224_finetuned_on_unlabelled_IA_with_snorkel_labels
  
  This model is a fine-tuned version of [facebook/convnext-base-224](https://huggingface.co/facebook/convnext-base-224) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3443
  - Precision: 0.9864
  - Recall: 0.9822
  - F1: 0.9843
  - Accuracy: 0.9884
  
  ## 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: 5e-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: 10
  - mixed_precision_training: Native AMP
  - label_smoothing_factor: 0.2
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.3611        | 1.0   | 2021  | 0.3467          | 0.9843    | 0.9729 | 0.9784 | 0.9842   |
  | 0.3524        | 2.0   | 4042  | 0.3453          | 0.9853    | 0.9790 | 0.9821 | 0.9868   |
  | 0.3466        | 3.0   | 6063  | 0.3438          | 0.9854    | 0.9847 | 0.9851 | 0.9889   |
  | 0.3433        | 4.0   | 8084  | 0.3434          | 0.9850    | 0.9808 | 0.9829 | 0.9873   |
  | 0.3404        | 5.0   | 10105 | 0.3459          | 0.9853    | 0.9790 | 0.9821 | 0.9868   |
  | 0.3384        | 6.0   | 12126 | 0.3453          | 0.9853    | 0.9790 | 0.9821 | 0.9868   |
  | 0.3382        | 7.0   | 14147 | 0.3437          | 0.9864    | 0.9822 | 0.9843 | 0.9884   |
  | 0.3358        | 8.0   | 16168 | 0.3441          | 0.9857    | 0.9829 | 0.9843 | 0.9884   |
  | 0.3349        | 9.0   | 18189 | 0.3448          | 0.9857    | 0.9829 | 0.9843 | 0.9884   |
  | 0.3325        | 10.0  | 20210 | 0.3443          | 0.9864    | 0.9822 | 0.9843 | 0.9884   |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  