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swiftformer-xs-DMAE

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Training in progress, epoch 34

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  1. README.md +40 -40
  2. model.safetensors +1 -1
  3. runs/Dec02_13-17-47_DESKTOP-SKBE9FB/events.out.tfevents.1733167068.DESKTOP-SKBE9FB.10800.0 +2 -2
  4. runs/Dec02_13-19-45_DESKTOP-SKBE9FB/events.out.tfevents.1733167186.DESKTOP-SKBE9FB.6360.0 +3 -0
  5. runs/Dec02_13-22-33_DESKTOP-SKBE9FB/events.out.tfevents.1733167354.DESKTOP-SKBE9FB.16864.0 +3 -0
  6. runs/Dec02_13-50-02_DESKTOP-SKBE9FB/events.out.tfevents.1733169003.DESKTOP-SKBE9FB.16100.0 +3 -0
  7. training_args.bin +1 -1
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.5434782608695652
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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
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [MBZUAI/swiftformer-xs](https://huggingface.co/MBZUAI/swiftformer-xs) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3591
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- - Accuracy: 0.5435
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  ## Model description
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@@ -51,7 +51,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.008
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -59,48 +59,48 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 64
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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: 40
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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 | 0.86 | 3 | 1.3591 | 0.5435 |
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- | No log | 2.0 | 7 | 1.2312 | 0.5435 |
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- | 1.2973 | 2.86 | 10 | 2.0533 | 0.3913 |
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- | 1.2973 | 4.0 | 14 | 3.3852 | 0.1304 |
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- | 1.2973 | 4.86 | 17 | 5.4029 | 0.2826 |
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- | 1.3932 | 6.0 | 21 | 6.7309 | 0.1522 |
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- | 1.3932 | 6.86 | 24 | 1.1894 | 0.4565 |
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- | 1.3932 | 8.0 | 28 | 1.3668 | 0.4565 |
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- | 1.224 | 8.86 | 31 | 1.4738 | 0.3043 |
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- | 1.224 | 10.0 | 35 | 3.3027 | 0.4783 |
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- | 1.224 | 10.86 | 38 | 1.5452 | 0.4565 |
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- | 1.1773 | 12.0 | 42 | 2.5106 | 0.3261 |
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- | 1.1773 | 12.86 | 45 | 2.3560 | 0.4565 |
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- | 1.1773 | 14.0 | 49 | 1.3445 | 0.5 |
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- | 1.2552 | 14.86 | 52 | 1.2641 | 0.4348 |
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- | 1.2552 | 16.0 | 56 | 1.2810 | 0.4130 |
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- | 1.2552 | 16.86 | 59 | 1.2486 | 0.4348 |
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- | 1.1857 | 18.0 | 63 | 1.3769 | 0.4565 |
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- | 1.1857 | 18.86 | 66 | 1.3311 | 0.3913 |
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- | 1.2054 | 20.0 | 70 | 1.3728 | 0.3043 |
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- | 1.2054 | 20.86 | 73 | 1.2437 | 0.4565 |
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- | 1.2054 | 22.0 | 77 | 1.2751 | 0.4130 |
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- | 1.2037 | 22.86 | 80 | 1.2529 | 0.4565 |
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- | 1.2037 | 24.0 | 84 | 1.2354 | 0.4565 |
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- | 1.2037 | 24.86 | 87 | 1.2389 | 0.4348 |
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- | 1.1888 | 26.0 | 91 | 1.2456 | 0.4348 |
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- | 1.1888 | 26.86 | 94 | 1.2312 | 0.4565 |
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- | 1.1888 | 28.0 | 98 | 1.2453 | 0.4565 |
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- | 1.1872 | 28.86 | 101 | 1.2507 | 0.4565 |
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- | 1.1872 | 30.0 | 105 | 1.2599 | 0.4130 |
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- | 1.1872 | 30.86 | 108 | 1.2493 | 0.4565 |
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- | 1.1796 | 32.0 | 112 | 1.2411 | 0.4565 |
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- | 1.1796 | 32.86 | 115 | 1.2362 | 0.4565 |
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- | 1.1796 | 34.0 | 119 | 1.2301 | 0.4565 |
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- | 1.199 | 34.29 | 120 | 1.2346 | 0.4565 |
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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: 0.45652173913043476
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  ---
26
 
27
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
31
 
32
  This model is a fine-tuned version of [MBZUAI/swiftformer-xs](https://huggingface.co/MBZUAI/swiftformer-xs) on the imagefolder dataset.
33
  It achieves the following results on the evaluation set:
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+ - Loss: 1.1969
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+ - Accuracy: 0.4565
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  ## Model description
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  ### Training hyperparameters
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53
  The following hyperparameters were used during training:
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+ - learning_rate: 0.05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
 
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  - total_train_batch_size: 64
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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: 0.01
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  - num_epochs: 40
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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 | 0.86 | 3 | 34874.7891 | 0.1087 |
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+ | No log | 2.0 | 7 | 415543488.0 | 0.4565 |
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+ | 107.6051 | 2.86 | 10 | 14879.4717 | 0.1087 |
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+ | 107.6051 | 4.0 | 14 | 68935.1875 | 0.1087 |
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+ | 107.6051 | 4.86 | 17 | 7599.6079 | 0.1087 |
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+ | 61.6907 | 6.0 | 21 | 1392.9758 | 0.1304 |
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+ | 61.6907 | 6.86 | 24 | 524.5536 | 0.1739 |
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+ | 61.6907 | 8.0 | 28 | 367.8024 | 0.1087 |
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+ | 9.2329 | 8.86 | 31 | 27.2661 | 0.4565 |
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+ | 9.2329 | 10.0 | 35 | 14.2920 | 0.1087 |
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+ | 9.2329 | 10.86 | 38 | 2.9737 | 0.3261 |
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+ | 4.2143 | 12.0 | 42 | 114.2135 | 0.3261 |
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+ | 4.2143 | 12.86 | 45 | 1.6271 | 0.3261 |
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+ | 4.2143 | 14.0 | 49 | 7.7918 | 0.4348 |
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+ | 1.8981 | 14.86 | 52 | 3.3329 | 0.3261 |
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+ | 1.8981 | 16.0 | 56 | 2.0198 | 0.3261 |
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+ | 1.8981 | 16.86 | 59 | 1.4194 | 0.3261 |
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+ | 1.5139 | 18.0 | 63 | 1.3169 | 0.4565 |
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+ | 1.5139 | 18.86 | 66 | 1.8718 | 0.3261 |
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+ | 1.7219 | 20.0 | 70 | 2.1572 | 0.1087 |
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+ | 1.7219 | 20.86 | 73 | 2.1683 | 0.3043 |
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+ | 1.7219 | 22.0 | 77 | 1.6241 | 0.4565 |
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+ | 1.5029 | 22.86 | 80 | 2.1474 | 0.4565 |
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+ | 1.5029 | 24.0 | 84 | 1.5354 | 0.4348 |
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+ | 1.5029 | 24.86 | 87 | 1.2864 | 0.4565 |
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+ | 1.3532 | 26.0 | 91 | 1.3014 | 0.3261 |
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+ | 1.3532 | 26.86 | 94 | 1.2604 | 0.4565 |
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+ | 1.3532 | 28.0 | 98 | 1.3335 | 0.3043 |
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+ | 1.2957 | 28.86 | 101 | 1.2444 | 0.4565 |
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+ | 1.2957 | 30.0 | 105 | 1.2858 | 0.3261 |
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+ | 1.2957 | 30.86 | 108 | 1.2190 | 0.4783 |
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+ | 1.2547 | 32.0 | 112 | 1.2271 | 0.4565 |
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+ | 1.2547 | 32.86 | 115 | 1.2194 | 0.4565 |
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+ | 1.2547 | 34.0 | 119 | 1.1941 | 0.4565 |
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+ | 1.2042 | 34.29 | 120 | 1.1969 | 0.4565 |
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  ### Framework versions
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