readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: flyswot_iiif
    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. -->
  
  # flyswot_iiif
  
  This model is a fine-tuned version of [facebook/convnext-base-224-22k](https://huggingface.co/facebook/convnext-base-224-22k) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 6.1280
  - F1: 0.0034
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 666
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 8
  - mixed_precision_training: Native AMP
  - label_smoothing_factor: 0.1
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 8.5184        | 0.26  | 500   | 7.9280          | 0.0005 |
  | 7.7409        | 0.52  | 1000  | 7.5824          | 0.0007 |
  | 7.4649        | 0.78  | 1500  | 7.3841          | 0.0010 |
  | 7.3285        | 1.04  | 2000  | 7.2652          | 0.0012 |
  | 7.1404        | 1.3   | 2500  | 7.1559          | 0.0014 |
  | 7.0322        | 1.56  | 3000  | 7.0551          | 0.0016 |
  | 6.9197        | 1.82  | 3500  | 6.9449          | 0.0019 |
  | 6.7822        | 2.09  | 4000  | 6.8773          | 0.0018 |
  | 6.6506        | 2.35  | 4500  | 6.7980          | 0.0020 |
  | 6.5811        | 2.61  | 5000  | 6.7382          | 0.0022 |
  | 6.538         | 2.87  | 5500  | 6.6582          | 0.0022 |
  | 6.4136        | 3.13  | 6000  | 6.6013          | 0.0024 |
  | 6.3325        | 3.39  | 6500  | 6.5369          | 0.0024 |
  | 6.2566        | 3.65  | 7000  | 6.4875          | 0.0025 |
  | 6.2285        | 3.91  | 7500  | 6.4342          | 0.0027 |
  | 6.1281        | 4.17  | 8000  | 6.4066          | 0.0027 |
  | 6.0762        | 4.43  | 8500  | 6.3674          | 0.0027 |
  | 6.0309        | 4.69  | 9000  | 6.3336          | 0.0027 |
  | 6.0123        | 4.95  | 9500  | 6.2932          | 0.0030 |
  | 5.9089        | 5.21  | 10000 | 6.2835          | 0.0029 |
  | 5.8901        | 5.47  | 10500 | 6.2481          | 0.0030 |
  | 5.86          | 5.74  | 11000 | 6.2295          | 0.0030 |
  | 5.8586        | 6.0   | 11500 | 6.2068          | 0.0033 |
  | 5.7768        | 6.26  | 12000 | 6.1937          | 0.0031 |
  | 5.7591        | 6.52  | 12500 | 6.1916          | 0.0032 |
  | 5.7443        | 6.78  | 13000 | 6.1579          | 0.0033 |
  | 5.7125        | 7.04  | 13500 | 6.1478          | 0.0033 |
  | 5.6751        | 7.3   | 14000 | 6.1379          | 0.0035 |
  | 5.6648        | 7.56  | 14500 | 6.1304          | 0.0035 |
  | 5.6644        | 7.82  | 15000 | 6.1280          | 0.0034 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.6
  