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PE_fb_w_v2

This model is a fine-tuned version of facebook/convnext-tiny-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Accuracy: 1.0

• F1: 1.0

• Precision: 1.0

• Recall: 1.0

• Loss: 0.0016

• Classification Report: precision recall f1-score support

       7       1.00      1.00      1.00        18
  

  accuracy 1.00 18 macro avg 1.00 1.00 1.00 18 weighted avg 1.00 1.00 1.00 18

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: 0.0005
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 4
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 6

Training results

       1       0.00      0.00      0.00         0
       7       1.00      0.83      0.91        18

accuracy                           0.83        18

macro avg 0.50 0.42 0.45 18 weighted avg 1.00 0.83 0.91 18 | | 0.0006 | 2.0 | 904 | 0.7222 | 0.2097 | 0.25 | 0.9306 | 1.1798 | precision recall f1-score support

       0       0.00      0.00      0.00         0
       1       0.00      0.00      0.00         0
       5       0.00      0.00      0.00         0
       7       1.00      0.72      0.84        18

accuracy                           0.72        18

macro avg 0.25 0.18 0.21 18 weighted avg 1.00 0.72 0.84 18 | | 0.0359 | 3.0 | 1356 | 0.8889 | 0.4706 | 0.5 | 0.9444 | 0.5522 | precision recall f1-score support

       5       0.00      0.00      0.00         0
       7       1.00      0.89      0.94        18

accuracy                           0.89        18

macro avg 0.50 0.44 0.47 18 weighted avg 1.00 0.89 0.94 18 | | 0.0057 | 4.0 | 1808 | 0.8889 | 0.3137 | 0.3333 | 0.9630 | 0.4023 | precision recall f1-score support

       0       0.00      0.00      0.00         0
       6       0.00      0.00      0.00         0
       7       1.00      0.89      0.94        18

accuracy                           0.89        18

macro avg 0.33 0.30 0.31 18 weighted avg 1.00 0.89 0.94 18 | | 0.0972 | 5.0 | 2260 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0117 | precision recall f1-score support

       7       1.00      1.00      1.00        18

accuracy                           1.00        18

macro avg 1.00 1.00 1.00 18 weighted avg 1.00 1.00 1.00 18 | | 0.0039 | 6.0 | 2712 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0016 | precision recall f1-score support

       7       1.00      1.00      1.00        18

accuracy                           1.00        18

macro avg 1.00 1.00 1.00 18 weighted avg 1.00 1.00 1.00 18 |

Framework versions

• Transformers 4.34.1
• Pytorch 2.1.0+cu118
• Datasets 2.14.5
• Tokenizers 0.14.1