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update model card README.md

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  1. README.md +16 -7
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@@ -3,7 +3,7 @@ license: apache-2.0
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  tags:
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  - generated_from_trainer
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  metrics:
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- - f1
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  model-index:
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  - name: vit-base-patch16-224
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  results: []
@@ -16,8 +16,8 @@ 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](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6731
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- - F1: 0.0
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  ## Model description
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@@ -45,13 +45,22 @@ 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: 1
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:---:|
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- | 0.7894 | 0.98 | 27 | 0.6731 | 0.0 |
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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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  model-index:
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  - name: vit-base-patch16-224
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  results: []
 
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  This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2817
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+ - Accuracy: 0.7205
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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 | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.8025 | 0.98 | 27 | 0.6852 | 0.6407 |
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+ | 0.5648 | 1.98 | 54 | 0.7587 | 0.6971 |
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+ | 0.2165 | 2.98 | 81 | 0.6410 | 0.7387 |
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+ | 0.0587 | 3.98 | 108 | 1.9350 | 0.5682 |
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+ | 0.041 | 4.98 | 135 | 0.9925 | 0.7348 |
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+ | 0.013 | 5.98 | 162 | 1.3159 | 0.6980 |
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+ | 0.025 | 6.98 | 189 | 1.4855 | 0.7456 |
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+ | 0.0243 | 7.98 | 216 | 1.4230 | 0.7489 |
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+ | 0.0016 | 8.98 | 243 | 1.2937 | 0.7117 |
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+ | 0.0026 | 9.98 | 270 | 1.2817 | 0.7205 |
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  ### Framework versions