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swiftformer-xs-DMAE

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swiftformer
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  1. README.md +39 -39
  2. model.safetensors +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: 0.43478260869565216
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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: 1.2103
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- - Accuracy: 0.4348
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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: 0.05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -66,41 +66,41 @@ 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 | 0.86 | 3 | 113.8089 | 0.1087 |
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- | No log | 2.0 | 7 | 719662.6875 | 0.1087 |
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- | 113.1437 | 2.86 | 10 | 3930.8594 | 0.1087 |
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- | 113.1437 | 4.0 | 14 | 57703.1484 | 0.1087 |
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- | 113.1437 | 4.86 | 17 | 1127.0548 | 0.3261 |
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- | 96.1157 | 6.0 | 21 | 131.2882 | 0.1087 |
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- | 96.1157 | 6.86 | 24 | 305.9370 | 0.0870 |
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- | 96.1157 | 8.0 | 28 | 209.0138 | 0.1087 |
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- | 38.8121 | 8.86 | 31 | 30.6911 | 0.1304 |
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- | 38.8121 | 10.0 | 35 | 7.7503 | 0.4565 |
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- | 38.8121 | 10.86 | 38 | 16.1361 | 0.3261 |
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- | 10.6492 | 12.0 | 42 | 7.8875 | 0.4565 |
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- | 10.6492 | 12.86 | 45 | 4.8321 | 0.4565 |
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- | 10.6492 | 14.0 | 49 | 8.2543 | 0.4565 |
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- | 3.6688 | 14.86 | 52 | 3.3603 | 0.4565 |
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- | 3.6688 | 16.0 | 56 | 3.9023 | 0.4565 |
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- | 3.6688 | 16.86 | 59 | 3.6221 | 0.4565 |
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- | 1.5847 | 18.0 | 63 | 3.2802 | 0.4565 |
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- | 1.5847 | 18.86 | 66 | 1.8639 | 0.4565 |
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- | 1.5235 | 20.0 | 70 | 2.5394 | 0.4565 |
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- | 1.5235 | 20.86 | 73 | 1.4062 | 0.4783 |
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- | 1.5235 | 22.0 | 77 | 1.4145 | 0.3913 |
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- | 1.3634 | 22.86 | 80 | 1.3275 | 0.4565 |
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- | 1.3634 | 24.0 | 84 | 1.3357 | 0.3478 |
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- | 1.3634 | 24.86 | 87 | 1.4708 | 0.4565 |
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- | 1.2807 | 26.0 | 91 | 1.2909 | 0.4565 |
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- | 1.2807 | 26.86 | 94 | 1.3445 | 0.4565 |
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- | 1.2807 | 28.0 | 98 | 1.2974 | 0.3696 |
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- | 1.2625 | 28.86 | 101 | 1.3482 | 0.4565 |
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- | 1.2625 | 30.0 | 105 | 1.2866 | 0.3478 |
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- | 1.2625 | 30.86 | 108 | 1.2364 | 0.4783 |
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- | 1.2472 | 32.0 | 112 | 1.2389 | 0.4130 |
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- | 1.2472 | 32.86 | 115 | 1.2459 | 0.3478 |
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- | 1.2472 | 34.0 | 119 | 1.2090 | 0.4348 |
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- | 1.2117 | 34.29 | 120 | 1.2103 | 0.4348 |
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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: 0.6956521739130435
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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 [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: 0.8074
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+ - Accuracy: 0.6957
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.005
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.86 | 3 | 1.3706 | 0.5435 |
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+ | No log | 2.0 | 7 | 1.1672 | 0.6304 |
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+ | 1.2937 | 2.86 | 10 | 1.2248 | 0.6087 |
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+ | 1.2937 | 4.0 | 14 | 2.6986 | 0.3478 |
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+ | 1.2937 | 4.86 | 17 | 2.6008 | 0.4565 |
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+ | 1.2355 | 6.0 | 21 | 1.8900 | 0.4130 |
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+ | 1.2355 | 6.86 | 24 | 1.5958 | 0.5 |
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+ | 1.2355 | 8.0 | 28 | 1.3847 | 0.5652 |
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+ | 1.1548 | 8.86 | 31 | 0.8762 | 0.7174 |
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+ | 1.1548 | 10.0 | 35 | 1.0871 | 0.5435 |
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+ | 1.1548 | 10.86 | 38 | 0.9779 | 0.5435 |
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+ | 1.0561 | 12.0 | 42 | 1.2454 | 0.5435 |
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+ | 1.0561 | 12.86 | 45 | 1.2277 | 0.5652 |
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+ | 1.0561 | 14.0 | 49 | 0.9527 | 0.6087 |
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+ | 1.0546 | 14.86 | 52 | 0.8797 | 0.6304 |
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+ | 1.0546 | 16.0 | 56 | 0.9479 | 0.6304 |
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+ | 1.0546 | 16.86 | 59 | 0.8696 | 0.6739 |
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+ | 0.9493 | 18.0 | 63 | 0.9348 | 0.6522 |
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+ | 0.9493 | 18.86 | 66 | 0.9890 | 0.5435 |
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+ | 0.9354 | 20.0 | 70 | 0.9073 | 0.5870 |
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+ | 0.9354 | 20.86 | 73 | 0.8763 | 0.6304 |
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+ | 0.9354 | 22.0 | 77 | 0.9592 | 0.6522 |
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+ | 0.8791 | 22.86 | 80 | 0.8940 | 0.6522 |
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+ | 0.8791 | 24.0 | 84 | 0.8165 | 0.6957 |
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+ | 0.8791 | 24.86 | 87 | 0.8249 | 0.6957 |
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+ | 0.8017 | 26.0 | 91 | 0.8946 | 0.6739 |
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+ | 0.8017 | 26.86 | 94 | 0.8210 | 0.6957 |
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+ | 0.8017 | 28.0 | 98 | 0.7654 | 0.7609 |
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+ | 0.8532 | 28.86 | 101 | 0.7492 | 0.7391 |
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+ | 0.8532 | 30.0 | 105 | 0.7725 | 0.6957 |
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+ | 0.8532 | 30.86 | 108 | 0.7932 | 0.7174 |
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+ | 0.8205 | 32.0 | 112 | 0.8129 | 0.7391 |
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+ | 0.8205 | 32.86 | 115 | 0.8089 | 0.6957 |
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+ | 0.8205 | 34.0 | 119 | 0.8151 | 0.6957 |
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+ | 0.8112 | 34.29 | 120 | 0.8074 | 0.6957 |
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  ### Framework versions
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