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panda992
/
fish_disease_datasets

Image Classification
Transformers
TensorBoard
Safetensors
vit
vision-transformer
aquaculture
fish-disease
Generated from Trainer
Eval Results
Model card Files
xet
Metrics Community
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Files changed (5) hide show
  1. README.md +9 -10
  2. model.safetensors +1 -1
  3. preprocessor_config.json +1 -1
  4. runs/May10_06-47-56_35deed949fff/events.out.tfevents.1746859688.35deed949fff.185.2 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -1,9 +1,8 @@
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  ---
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  library_name: transformers
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  license: apache-2.0
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- base_model: google/vit-base-patch16-224-in21k
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  tags:
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- - image-classification
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  - generated_from_trainer
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  metrics:
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  - accuracy
@@ -17,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # fish_disease_datasets
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- This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the fish_disease_datasets dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1053
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- - Accuracy: 0.9728
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  ## Model description
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@@ -52,11 +51,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 0.7341 | 0.7634 | 100 | 0.4725 | 0.8995 |
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- | 0.4232 | 1.5267 | 200 | 0.2454 | 0.9538 |
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- | 0.1134 | 2.2901 | 300 | 0.1689 | 0.9755 |
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- | 0.2237 | 3.0534 | 400 | 0.1639 | 0.9592 |
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- | 0.1431 | 3.8168 | 500 | 0.1053 | 0.9728 |
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  ### Framework versions
 
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  ---
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  library_name: transformers
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  license: apache-2.0
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+ base_model: panda992/fish_disease_datasets
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  tags:
 
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  - generated_from_trainer
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  metrics:
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  - accuracy
 
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  # fish_disease_datasets
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+ This model is a fine-tuned version of [panda992/fish_disease_datasets](https://huggingface.co/panda992/fish_disease_datasets) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0675
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+ - Accuracy: 0.9810
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.2052 | 0.7634 | 100 | 0.1684 | 0.9484 |
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+ | 0.05 | 1.5267 | 200 | 0.1600 | 0.9592 |
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+ | 0.0579 | 2.2901 | 300 | 0.1619 | 0.9511 |
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+ | 0.1181 | 3.0534 | 400 | 0.0685 | 0.9810 |
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+ | 0.1321 | 3.8168 | 500 | 0.0675 | 0.9810 |
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  ### Framework versions
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