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vit-msn-small-beta-fia-manually-enhanced-HSV_test_3

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  1. README.md +32 -32
  2. model.safetensors +1 -1
  3. runs/Jan27_17-20-31_db1093ce036b/events.out.tfevents.1737998436.db1093ce036b.224.7 +2 -2
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8661971830985915
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Melo1512/vit-msn-small-beta-fia-manually-enhanced-HSV_test_2](https://huggingface.co/Melo1512/vit-msn-small-beta-fia-manually-enhanced-HSV_test_2) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5505
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- - Accuracy: 0.8662
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  ## Model description
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@@ -60,7 +60,7 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 256
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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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- - lr_scheduler_warmup_ratio: 0.33
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  - num_epochs: 50
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  - label_smoothing_factor: 0.1
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@@ -69,34 +69,34 @@ 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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  | No log | 0.5714 | 1 | 0.5123 | 0.8873 |
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- | No log | 1.7143 | 3 | 0.5148 | 0.8873 |
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- | No log | 2.8571 | 5 | 0.5252 | 0.8803 |
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- | No log | 4.0 | 7 | 0.5444 | 0.8732 |
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- | No log | 4.5714 | 8 | 0.5492 | 0.8662 |
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- | 0.4298 | 5.7143 | 10 | 0.5352 | 0.8732 |
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- | 0.4298 | 6.8571 | 12 | 0.5188 | 0.8873 |
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- | 0.4298 | 8.0 | 14 | 0.5233 | 0.8662 |
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- | 0.4298 | 8.5714 | 15 | 0.5289 | 0.8662 |
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- | 0.4298 | 9.7143 | 17 | 0.5421 | 0.8732 |
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- | 0.4298 | 10.8571 | 19 | 0.5347 | 0.8732 |
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- | 0.4391 | 12.0 | 21 | 0.5349 | 0.8662 |
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- | 0.4391 | 12.5714 | 22 | 0.5353 | 0.8732 |
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- | 0.4391 | 13.7143 | 24 | 0.5448 | 0.8662 |
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- | 0.4391 | 14.8571 | 26 | 0.5444 | 0.8662 |
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- | 0.4391 | 16.0 | 28 | 0.5299 | 0.8662 |
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- | 0.4391 | 16.5714 | 29 | 0.5249 | 0.8592 |
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- | 0.4348 | 17.7143 | 31 | 0.5256 | 0.8592 |
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- | 0.4348 | 18.8571 | 33 | 0.5453 | 0.8732 |
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- | 0.4348 | 20.0 | 35 | 0.5724 | 0.8451 |
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- | 0.4348 | 20.5714 | 36 | 0.5856 | 0.8380 |
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- | 0.4348 | 21.7143 | 38 | 0.5779 | 0.8380 |
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- | 0.4205 | 22.8571 | 40 | 0.5520 | 0.8732 |
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- | 0.4205 | 24.0 | 42 | 0.5444 | 0.8732 |
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- | 0.4205 | 24.5714 | 43 | 0.5434 | 0.8732 |
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- | 0.4205 | 25.7143 | 45 | 0.5476 | 0.8662 |
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- | 0.4205 | 26.8571 | 47 | 0.5498 | 0.8662 |
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- | 0.4205 | 28.0 | 49 | 0.5505 | 0.8662 |
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- | 0.4262 | 28.5714 | 50 | 0.5505 | 0.8662 |
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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: 0.8732394366197183
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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 [Melo1512/vit-msn-small-beta-fia-manually-enhanced-HSV_test_2](https://huggingface.co/Melo1512/vit-msn-small-beta-fia-manually-enhanced-HSV_test_2) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5558
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+ - Accuracy: 0.8732
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  ## Model description
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  - total_train_batch_size: 256
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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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+ - lr_scheduler_warmup_ratio: 0.15
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  - num_epochs: 50
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  - label_smoothing_factor: 0.1
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-------:|:----:|:---------------:|:--------:|
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  | No log | 0.5714 | 1 | 0.5123 | 0.8873 |
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+ | No log | 1.7143 | 3 | 0.5495 | 0.8662 |
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+ | No log | 2.8571 | 5 | 0.6080 | 0.8592 |
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+ | No log | 4.0 | 7 | 0.5591 | 0.8732 |
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+ | No log | 4.5714 | 8 | 0.5464 | 0.8732 |
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+ | 0.4241 | 5.7143 | 10 | 0.5982 | 0.8451 |
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+ | 0.4241 | 6.8571 | 12 | 0.6497 | 0.8169 |
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+ | 0.4241 | 8.0 | 14 | 0.5928 | 0.8521 |
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+ | 0.4241 | 8.5714 | 15 | 0.5711 | 0.8521 |
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+ | 0.4241 | 9.7143 | 17 | 0.5468 | 0.8732 |
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+ | 0.4241 | 10.8571 | 19 | 0.5483 | 0.8521 |
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+ | 0.4152 | 12.0 | 21 | 0.5783 | 0.8451 |
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+ | 0.4152 | 12.5714 | 22 | 0.5835 | 0.8451 |
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+ | 0.4152 | 13.7143 | 24 | 0.5668 | 0.8451 |
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+ | 0.4152 | 14.8571 | 26 | 0.5556 | 0.8451 |
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+ | 0.4152 | 16.0 | 28 | 0.5564 | 0.8451 |
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+ | 0.4152 | 16.5714 | 29 | 0.5591 | 0.8451 |
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+ | 0.4367 | 17.7143 | 31 | 0.5619 | 0.8592 |
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+ | 0.4367 | 18.8571 | 33 | 0.5809 | 0.8592 |
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+ | 0.4367 | 20.0 | 35 | 0.5810 | 0.8662 |
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+ | 0.4367 | 20.5714 | 36 | 0.5768 | 0.8662 |
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+ | 0.4367 | 21.7143 | 38 | 0.5591 | 0.8732 |
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+ | 0.4241 | 22.8571 | 40 | 0.5452 | 0.8732 |
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+ | 0.4241 | 24.0 | 42 | 0.5387 | 0.8732 |
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+ | 0.4241 | 24.5714 | 43 | 0.5398 | 0.8732 |
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+ | 0.4241 | 25.7143 | 45 | 0.5458 | 0.8732 |
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+ | 0.4241 | 26.8571 | 47 | 0.5509 | 0.8732 |
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+ | 0.4241 | 28.0 | 49 | 0.5550 | 0.8732 |
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+ | 0.4171 | 28.5714 | 50 | 0.5558 | 0.8732 |
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  ### Framework versions
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