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hushem_1x_deit_tiny_sgd_lr001_fold1

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  1. README.md +53 -39
  2. model.safetensors +1 -1
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: 0.28888888888888886
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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 [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5248
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- - Accuracy: 0.2889
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  ## Model description
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@@ -56,8 +56,6 @@ The following hyperparameters were used during training:
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
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- - gradient_accumulation_steps: 4
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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: linear
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  - lr_scheduler_warmup_ratio: 0.1
@@ -67,40 +65,56 @@ 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 | 0.67 | 1 | 1.6558 | 0.2667 |
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- | No log | 2.0 | 3 | 1.6426 | 0.2667 |
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- | No log | 2.67 | 4 | 1.6354 | 0.2667 |
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- | No log | 4.0 | 6 | 1.6235 | 0.2667 |
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- | No log | 4.67 | 7 | 1.6181 | 0.2667 |
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- | No log | 6.0 | 9 | 1.6074 | 0.2667 |
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- | 1.5585 | 6.67 | 10 | 1.6024 | 0.2667 |
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- | 1.5585 | 8.0 | 12 | 1.5928 | 0.2667 |
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- | 1.5585 | 8.67 | 13 | 1.5878 | 0.2667 |
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- | 1.5585 | 10.0 | 15 | 1.5809 | 0.2667 |
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- | 1.5585 | 10.67 | 16 | 1.5768 | 0.2667 |
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- | 1.5585 | 12.0 | 18 | 1.5710 | 0.2667 |
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- | 1.5585 | 12.67 | 19 | 1.5672 | 0.2667 |
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- | 1.4895 | 14.0 | 21 | 1.5624 | 0.2667 |
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- | 1.4895 | 14.67 | 22 | 1.5591 | 0.2667 |
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- | 1.4895 | 16.0 | 24 | 1.5545 | 0.2667 |
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- | 1.4895 | 16.67 | 25 | 1.5518 | 0.2667 |
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- | 1.4895 | 18.0 | 27 | 1.5474 | 0.2667 |
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- | 1.4895 | 18.67 | 28 | 1.5453 | 0.2667 |
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- | 1.4465 | 20.0 | 30 | 1.5417 | 0.2667 |
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- | 1.4465 | 20.67 | 31 | 1.5399 | 0.2667 |
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- | 1.4465 | 22.0 | 33 | 1.5368 | 0.2667 |
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- | 1.4465 | 22.67 | 34 | 1.5352 | 0.2667 |
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- | 1.4465 | 24.0 | 36 | 1.5328 | 0.2667 |
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- | 1.4465 | 24.67 | 37 | 1.5316 | 0.2667 |
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- | 1.4465 | 26.0 | 39 | 1.5298 | 0.2889 |
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- | 1.4141 | 26.67 | 40 | 1.5290 | 0.2889 |
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- | 1.4141 | 28.0 | 42 | 1.5277 | 0.2889 |
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- | 1.4141 | 28.67 | 43 | 1.5270 | 0.2889 |
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- | 1.4141 | 30.0 | 45 | 1.5259 | 0.2889 |
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- | 1.4141 | 30.67 | 46 | 1.5255 | 0.2889 |
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- | 1.4141 | 32.0 | 48 | 1.5251 | 0.2889 |
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- | 1.4141 | 32.67 | 49 | 1.5249 | 0.2889 |
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- | 1.4085 | 33.33 | 50 | 1.5248 | 0.2889 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.3111111111111111
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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 [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.4305
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+ - Accuracy: 0.3111
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  ## Model description
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
 
 
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 6 | 1.6118 | 0.1778 |
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+ | 1.6924 | 2.0 | 12 | 1.5735 | 0.2222 |
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+ | 1.6924 | 3.0 | 18 | 1.5416 | 0.2222 |
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+ | 1.5478 | 4.0 | 24 | 1.5201 | 0.2444 |
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+ | 1.5093 | 5.0 | 30 | 1.4995 | 0.2889 |
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+ | 1.5093 | 6.0 | 36 | 1.4836 | 0.2889 |
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+ | 1.4614 | 7.0 | 42 | 1.4737 | 0.2889 |
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+ | 1.4614 | 8.0 | 48 | 1.4656 | 0.2889 |
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+ | 1.3895 | 9.0 | 54 | 1.4578 | 0.2222 |
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+ | 1.4002 | 10.0 | 60 | 1.4519 | 0.2667 |
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+ | 1.4002 | 11.0 | 66 | 1.4464 | 0.2667 |
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+ | 1.3595 | 12.0 | 72 | 1.4429 | 0.2667 |
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+ | 1.3595 | 13.0 | 78 | 1.4392 | 0.2667 |
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+ | 1.3506 | 14.0 | 84 | 1.4366 | 0.2222 |
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+ | 1.2804 | 15.0 | 90 | 1.4347 | 0.2 |
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+ | 1.2804 | 16.0 | 96 | 1.4330 | 0.2 |
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+ | 1.2746 | 17.0 | 102 | 1.4333 | 0.2667 |
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+ | 1.2746 | 18.0 | 108 | 1.4332 | 0.2667 |
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+ | 1.2774 | 19.0 | 114 | 1.4327 | 0.2667 |
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+ | 1.2547 | 20.0 | 120 | 1.4313 | 0.2667 |
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+ | 1.2547 | 21.0 | 126 | 1.4295 | 0.2667 |
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+ | 1.2313 | 22.0 | 132 | 1.4282 | 0.2889 |
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+ | 1.2313 | 23.0 | 138 | 1.4285 | 0.2889 |
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+ | 1.2194 | 24.0 | 144 | 1.4285 | 0.2889 |
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+ | 1.2083 | 25.0 | 150 | 1.4272 | 0.2889 |
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+ | 1.2083 | 26.0 | 156 | 1.4286 | 0.3111 |
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+ | 1.1973 | 27.0 | 162 | 1.4278 | 0.3111 |
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+ | 1.1973 | 28.0 | 168 | 1.4278 | 0.3111 |
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+ | 1.1964 | 29.0 | 174 | 1.4276 | 0.3111 |
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+ | 1.2006 | 30.0 | 180 | 1.4293 | 0.3111 |
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+ | 1.2006 | 31.0 | 186 | 1.4290 | 0.3111 |
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+ | 1.1662 | 32.0 | 192 | 1.4295 | 0.3111 |
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+ | 1.1662 | 33.0 | 198 | 1.4297 | 0.3111 |
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+ | 1.1889 | 34.0 | 204 | 1.4294 | 0.3111 |
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+ | 1.1683 | 35.0 | 210 | 1.4293 | 0.3111 |
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+ | 1.1683 | 36.0 | 216 | 1.4299 | 0.3111 |
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+ | 1.1652 | 37.0 | 222 | 1.4302 | 0.3111 |
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+ | 1.1652 | 38.0 | 228 | 1.4307 | 0.3111 |
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+ | 1.1321 | 39.0 | 234 | 1.4308 | 0.3111 |
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+ | 1.1584 | 40.0 | 240 | 1.4306 | 0.3111 |
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+ | 1.1584 | 41.0 | 246 | 1.4304 | 0.3111 |
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+ | 1.1553 | 42.0 | 252 | 1.4305 | 0.3111 |
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+ | 1.1553 | 43.0 | 258 | 1.4305 | 0.3111 |
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+ | 1.168 | 44.0 | 264 | 1.4305 | 0.3111 |
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+ | 1.1533 | 45.0 | 270 | 1.4305 | 0.3111 |
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+ | 1.1533 | 46.0 | 276 | 1.4305 | 0.3111 |
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+ | 1.1682 | 47.0 | 282 | 1.4305 | 0.3111 |
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+ | 1.1682 | 48.0 | 288 | 1.4305 | 0.3111 |
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+ | 1.1255 | 49.0 | 294 | 1.4305 | 0.3111 |
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+ | 1.1698 | 50.0 | 300 | 1.4305 | 0.3111 |
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  ### Framework versions
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