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End of training

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  1. README.md +33 -19
  2. model.safetensors +1 -1
README.md CHANGED
@@ -17,7 +17,7 @@ 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 the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5563
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  ## Model description
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@@ -40,8 +40,6 @@ The following hyperparameters were used during training:
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 69
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- - gradient_accumulation_steps: 8
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- - total_train_batch_size: 128
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.1
@@ -51,22 +49,38 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.6302 | 0.88 | 20 | 0.5969 |
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- | 0.5182 | 1.76 | 40 | 0.5321 |
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- | 0.4872 | 2.64 | 60 | 0.5341 |
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- | 0.4641 | 3.52 | 80 | 0.5578 |
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- | 0.3737 | 4.4 | 100 | 0.5354 |
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- | 0.2761 | 5.27 | 120 | 0.5345 |
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- | 0.3207 | 6.15 | 140 | 0.5338 |
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- | 0.391 | 7.03 | 160 | 0.5245 |
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- | 0.282 | 7.91 | 180 | 0.5035 |
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- | 0.2945 | 8.79 | 200 | 0.5162 |
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- | 0.2355 | 9.67 | 220 | 0.5400 |
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- | 0.2032 | 10.55 | 240 | 0.5418 |
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- | 0.1749 | 11.43 | 260 | 0.5516 |
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- | 0.2126 | 12.31 | 280 | 0.5357 |
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- | 0.1701 | 13.19 | 300 | 0.5828 |
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- | 0.2586 | 14.07 | 320 | 0.5563 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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 the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5429
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  ## Model description
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 69
 
 
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.1
 
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.7599 | 0.11 | 20 | 0.7105 |
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+ | 0.6535 | 0.22 | 40 | 0.6561 |
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+ | 0.6191 | 0.33 | 60 | 0.6045 |
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+ | 0.7219 | 0.44 | 80 | 0.5976 |
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+ | 0.62 | 0.55 | 100 | 0.5781 |
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+ | 0.5249 | 0.66 | 120 | 0.5743 |
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+ | 0.5934 | 0.77 | 140 | 0.5684 |
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+ | 0.4143 | 0.88 | 160 | 0.5522 |
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+ | 0.4472 | 0.99 | 180 | 0.5645 |
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+ | 0.3507 | 1.1 | 200 | 0.5784 |
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+ | 0.4165 | 1.21 | 220 | 0.5796 |
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+ | 0.2822 | 1.32 | 240 | 0.5867 |
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+ | 0.4765 | 1.43 | 260 | 0.5446 |
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+ | 0.4557 | 1.54 | 280 | 0.5739 |
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+ | 0.4087 | 1.65 | 300 | 0.5292 |
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+ | 0.4181 | 1.76 | 320 | 0.5182 |
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+ | 0.6616 | 1.87 | 340 | 0.5328 |
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+ | 0.48 | 1.98 | 360 | 0.5282 |
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+ | 0.2159 | 2.09 | 380 | 0.5457 |
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+ | 0.5038 | 2.2 | 400 | 0.5832 |
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+ | 0.6434 | 2.31 | 420 | 0.5667 |
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+ | 0.4566 | 2.42 | 440 | 0.5128 |
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+ | 0.2972 | 2.53 | 460 | 0.5475 |
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+ | 0.5094 | 2.64 | 480 | 0.5536 |
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+ | 0.4807 | 2.75 | 500 | 0.5512 |
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+ | 0.3666 | 2.86 | 520 | 0.5128 |
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+ | 0.38 | 2.97 | 540 | 0.5499 |
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+ | 0.3496 | 3.08 | 560 | 0.5129 |
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+ | 0.3503 | 3.19 | 580 | 0.5480 |
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+ | 0.4435 | 3.3 | 600 | 0.5918 |
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+ | 0.2163 | 3.41 | 620 | 0.5558 |
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+ | 0.4316 | 3.52 | 640 | 0.5429 |
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  ### Framework versions
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