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hlillemark
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my_awesome_food_model

Image Classification
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vit
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  1. README.md +15 -8
  2. model.safetensors +1 -1
  3. runs/Jan23_14-32-23_parka/events.out.tfevents.1706051044.parka.3337075.1 +3 -0
  4. runs/Jan23_15-23-21_parka/events.out.tfevents.1706052202.parka.3337075.2 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ 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: 4.3629
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- - Accuracy: 0.437
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  ## Model description
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@@ -46,15 +46,22 @@ The following hyperparameters were used during training:
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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: 0.1
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- - num_epochs: 3
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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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- | No log | 1.0 | 2 | 4.5210 | 0.036 |
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- | No log | 2.0 | 4 | 4.4151 | 0.278 |
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- | No log | 3.0 | 6 | 4.3629 | 0.437 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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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: 3.8640
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+ - Accuracy: 0.573
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  ## Model description
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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: 0.1
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+ - num_epochs: 10
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  ### Training results
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+ | Training Loss | Epoch | Step | Accuracy | Validation Loss |
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+ |:-------------:|:-----:|:----:|:--------:|:---------------:|
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+ | No log | 1.0 | 2 | 0.036 | 4.5210 |
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+ | No log | 2.0 | 4 | 0.278 | 4.4151 |
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+ | No log | 3.0 | 6 | 0.437 | 4.3629 |
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+ | No log | 4.0 | 8 | 4.2960 | 0.547 |
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+ | 4.3122 | 5.0 | 10 | 4.1697 | 0.589 |
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+ | 4.3122 | 6.0 | 12 | 4.0601 | 0.568 |
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+ | 4.3122 | 7.0 | 14 | 3.9770 | 0.521 |
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+ | 4.3122 | 8.0 | 16 | 3.9177 | 0.539 |
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+ | 4.3122 | 9.0 | 18 | 3.8843 | 0.545 |
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+ | 3.9792 | 10.0 | 20 | 3.8640 | 0.573 |
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  ### Framework versions
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