readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: resnet-50_finetuned
    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. -->
  
  # resnet-50_finetuned
  
  This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7209
  - Precision: 0.3702
  - Recall: 0.5
  - F1: 0.4254
  - Accuracy: 0.7404
  
  ## 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: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 46   | 0.6599          | 0.3702    | 0.5    | 0.4254 | 0.7404   |
  | No log        | 2.0   | 92   | 0.6725          | 0.3702    | 0.5    | 0.4254 | 0.7404   |
  | No log        | 3.0   | 138  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
  | No log        | 4.0   | 184  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
  | No log        | 5.0   | 230  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
  | No log        | 6.0   | 276  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
  | No log        | 7.0   | 322  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
  | No log        | 8.0   | 368  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
  | No log        | 9.0   | 414  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
  | No log        | 10.0  | 460  | 0.7209          | 0.3702    | 0.5    | 0.4254 | 0.7404   |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  