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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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  1. README.md +7 -8
  2. model.safetensors +1 -1
  3. runs/May10_06-15-04_35deed949fff/events.out.tfevents.1746857717.35deed949fff.185.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1304
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- - Accuracy: 0.9701
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  ## Model description
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@@ -51,16 +51,15 @@ 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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- | 0.7452 | 0.7634 | 100 | 0.6666 | 0.8424 |
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- | 0.4274 | 1.5267 | 200 | 0.3042 | 0.9185 |
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- | 0.2164 | 2.2901 | 300 | 0.2098 | 0.9538 |
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- | 0.1461 | 3.0534 | 400 | 0.1556 | 0.9511 |
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- | 0.1148 | 3.8168 | 500 | 0.1304 | 0.9701 |
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  ### Framework versions
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  - Transformers 4.51.3
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  - Pytorch 2.6.0+cu124
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- - Datasets 3.6.0
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  - Tokenizers 0.21.1
 
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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 an unknown 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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  | 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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  - Transformers 4.51.3
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  - Pytorch 2.6.0+cu124
 
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  - Tokenizers 0.21.1
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