Model save
Browse files- README.md +21 -10
- all_results.json +10 -10
- eval_results.json +5 -6
- model.safetensors +1 -1
- runs/Dec01_13-41-24_610b2a9400b8/events.out.tfevents.1701438092.610b2a9400b8.3653.8 +3 -0
- train_results.json +5 -5
- trainer_state.json +111 -111
- training_args.bin +1 -1
README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Accuracy: 0.
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## Model description
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs:
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9887218045112782
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0732
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- Accuracy: 0.9887
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## Model description
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 50
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.2908 | 2.94 | 100 | 0.1524 | 0.9511 |
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| 0.1806 | 5.88 | 200 | 0.1269 | 0.9586 |
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| 0.1135 | 8.82 | 300 | 0.0720 | 0.9774 |
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| 0.1061 | 11.76 | 400 | 0.1519 | 0.9624 |
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| 0.0816 | 14.71 | 500 | 0.1845 | 0.9398 |
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| 0.0815 | 17.65 | 600 | 0.0966 | 0.9737 |
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| 0.0741 | 20.59 | 700 | 0.1029 | 0.9812 |
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| 0.0423 | 23.53 | 800 | 0.1519 | 0.9699 |
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| 0.0468 | 26.47 | 900 | 0.0757 | 0.9850 |
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| 0.0249 | 29.41 | 1000 | 0.0859 | 0.9850 |
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| 0.0443 | 32.35 | 1100 | 0.0878 | 0.9774 |
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| 0.0291 | 35.29 | 1200 | 0.0487 | 0.9887 |
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| 0.0263 | 38.24 | 1300 | 0.0643 | 0.9887 |
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| 0.0239 | 41.18 | 1400 | 0.1042 | 0.9774 |
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| 0.0331 | 44.12 | 1500 | 0.0679 | 0.9887 |
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| 0.0103 | 47.06 | 1600 | 0.0723 | 0.9887 |
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| 0.0131 | 50.0 | 1700 | 0.0732 | 0.9887 |
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### Framework versions
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all_results.json
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