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swiftformer-xs-dmae-va-U-80

Image Classification
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swiftformer
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  1. README.md +75 -39
  2. model.safetensors +1 -1
  3. runs/Feb01_19-27-47_b2db6ba6b423/events.out.tfevents.1706815678.b2db6ba6b423.7182.0 +2 -2
README.md CHANGED
@@ -16,7 +16,7 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6494
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  - Accuracy: 0.8165
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  ## Model description
@@ -45,49 +45,85 @@ 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: 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 | 0.9 | 7 | 1.3781 | 0.3486 |
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- | 1.3901 | 1.94 | 15 | 1.3538 | 0.3303 |
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- | 1.3561 | 2.97 | 23 | 1.3091 | 0.3761 |
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- | 1.2933 | 4.0 | 31 | 1.2623 | 0.4220 |
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- | 1.2933 | 4.9 | 38 | 1.2065 | 0.5138 |
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- | 1.2274 | 5.94 | 46 | 1.1353 | 0.5413 |
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- | 1.1686 | 6.97 | 54 | 1.0854 | 0.6147 |
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- | 1.097 | 8.0 | 62 | 1.0489 | 0.6330 |
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- | 1.097 | 8.9 | 69 | 1.0185 | 0.6606 |
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- | 1.0349 | 9.94 | 77 | 0.9682 | 0.6422 |
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- | 1.0161 | 10.97 | 85 | 0.9511 | 0.6055 |
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- | 0.9633 | 12.0 | 93 | 0.9009 | 0.6606 |
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- | 0.939 | 12.9 | 100 | 0.9055 | 0.6514 |
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- | 0.939 | 13.94 | 108 | 0.8781 | 0.6697 |
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- | 0.9036 | 14.97 | 116 | 0.8494 | 0.7248 |
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- | 0.8687 | 16.0 | 124 | 0.8503 | 0.6789 |
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- | 0.8535 | 16.9 | 131 | 0.8164 | 0.7248 |
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- | 0.8535 | 17.94 | 139 | 0.7883 | 0.7615 |
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- | 0.8306 | 18.97 | 147 | 0.7667 | 0.7615 |
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- | 0.8047 | 20.0 | 155 | 0.7600 | 0.7523 |
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- | 0.7735 | 20.9 | 162 | 0.7331 | 0.7615 |
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- | 0.784 | 21.94 | 170 | 0.7295 | 0.7523 |
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- | 0.784 | 22.97 | 178 | 0.7281 | 0.7431 |
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- | 0.7596 | 24.0 | 186 | 0.7045 | 0.7615 |
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- | 0.7609 | 24.9 | 193 | 0.6915 | 0.7706 |
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- | 0.7307 | 25.94 | 201 | 0.6970 | 0.8073 |
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- | 0.7307 | 26.97 | 209 | 0.6796 | 0.7615 |
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- | 0.7263 | 28.0 | 217 | 0.6615 | 0.7706 |
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- | 0.6933 | 28.9 | 224 | 0.6628 | 0.7798 |
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- | 0.6914 | 29.94 | 232 | 0.6596 | 0.8073 |
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- | 0.7192 | 30.97 | 240 | 0.6453 | 0.7982 |
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- | 0.7192 | 32.0 | 248 | 0.6569 | 0.7798 |
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- | 0.6956 | 32.9 | 255 | 0.6494 | 0.8165 |
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- | 0.7037 | 33.94 | 263 | 0.6478 | 0.8073 |
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- | 0.669 | 34.97 | 271 | 0.6415 | 0.7798 |
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- | 0.669 | 36.0 | 279 | 0.6441 | 0.7890 |
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- | 0.6715 | 36.13 | 280 | 0.6445 | 0.7798 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
16
 
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  This model is a fine-tuned version of [MBZUAI/swiftformer-xs](https://huggingface.co/MBZUAI/swiftformer-xs) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4359
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  - Accuracy: 0.8165
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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: 80
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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 | 0.9 | 7 | 1.3863 | 0.2844 |
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+ | 1.4158 | 1.94 | 15 | 1.3760 | 0.3119 |
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+ | 1.3853 | 2.97 | 23 | 1.3548 | 0.3853 |
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+ | 1.3745 | 4.0 | 31 | 1.3327 | 0.3394 |
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+ | 1.3745 | 4.9 | 38 | 1.2938 | 0.4220 |
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+ | 1.3435 | 5.94 | 46 | 1.2450 | 0.4679 |
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+ | 1.2681 | 6.97 | 54 | 1.1933 | 0.5596 |
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+ | 1.1803 | 8.0 | 62 | 1.1410 | 0.4771 |
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+ | 1.1803 | 8.9 | 69 | 1.1014 | 0.5046 |
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+ | 1.1277 | 9.94 | 77 | 1.0785 | 0.5321 |
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+ | 1.0674 | 10.97 | 85 | 1.0440 | 0.5596 |
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+ | 1.0353 | 12.0 | 93 | 0.9962 | 0.5780 |
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+ | 0.9859 | 12.9 | 100 | 0.9700 | 0.5872 |
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+ | 0.9859 | 13.94 | 108 | 0.9402 | 0.6422 |
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+ | 0.9397 | 14.97 | 116 | 0.9215 | 0.6239 |
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+ | 0.8959 | 16.0 | 124 | 0.8745 | 0.6606 |
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+ | 0.8663 | 16.9 | 131 | 0.8561 | 0.6697 |
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+ | 0.8663 | 17.94 | 139 | 0.8182 | 0.6789 |
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+ | 0.8405 | 18.97 | 147 | 0.8168 | 0.6514 |
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+ | 0.8093 | 20.0 | 155 | 0.8039 | 0.6789 |
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+ | 0.7396 | 20.9 | 162 | 0.7478 | 0.7064 |
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+ | 0.7588 | 21.94 | 170 | 0.7237 | 0.6972 |
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+ | 0.7588 | 22.97 | 178 | 0.7031 | 0.7156 |
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+ | 0.7189 | 24.0 | 186 | 0.6956 | 0.6972 |
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+ | 0.7111 | 24.9 | 193 | 0.6749 | 0.7248 |
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+ | 0.6577 | 25.94 | 201 | 0.6758 | 0.6972 |
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+ | 0.6577 | 26.97 | 209 | 0.6429 | 0.7339 |
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+ | 0.6681 | 28.0 | 217 | 0.6451 | 0.7064 |
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+ | 0.6238 | 28.9 | 224 | 0.6368 | 0.7339 |
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+ | 0.6136 | 29.94 | 232 | 0.6233 | 0.7706 |
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+ | 0.5934 | 30.97 | 240 | 0.6161 | 0.7706 |
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+ | 0.5934 | 32.0 | 248 | 0.6268 | 0.7431 |
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+ | 0.5807 | 32.9 | 255 | 0.5879 | 0.7982 |
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+ | 0.575 | 33.94 | 263 | 0.5772 | 0.7706 |
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+ | 0.5409 | 34.97 | 271 | 0.5703 | 0.7798 |
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+ | 0.5409 | 36.0 | 279 | 0.5603 | 0.7890 |
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+ | 0.553 | 36.9 | 286 | 0.5560 | 0.8073 |
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+ | 0.515 | 37.94 | 294 | 0.5639 | 0.7706 |
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+ | 0.5424 | 38.97 | 302 | 0.5483 | 0.7890 |
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+ | 0.5193 | 40.0 | 310 | 0.5505 | 0.7798 |
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+ | 0.5193 | 40.9 | 317 | 0.5323 | 0.8073 |
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+ | 0.5123 | 41.94 | 325 | 0.5257 | 0.7982 |
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+ | 0.4719 | 42.97 | 333 | 0.5270 | 0.7798 |
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+ | 0.4583 | 44.0 | 341 | 0.5305 | 0.7706 |
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+ | 0.4583 | 44.9 | 348 | 0.5282 | 0.7798 |
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+ | 0.4568 | 45.94 | 356 | 0.5178 | 0.7890 |
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+ | 0.4717 | 46.97 | 364 | 0.4945 | 0.7982 |
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+ | 0.4587 | 48.0 | 372 | 0.4978 | 0.7982 |
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+ | 0.4587 | 48.9 | 379 | 0.4888 | 0.7890 |
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+ | 0.4314 | 49.94 | 387 | 0.4867 | 0.7982 |
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+ | 0.4389 | 50.97 | 395 | 0.4739 | 0.7890 |
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+ | 0.4115 | 52.0 | 403 | 0.4844 | 0.7982 |
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+ | 0.4323 | 52.9 | 410 | 0.4819 | 0.7982 |
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+ | 0.4323 | 53.94 | 418 | 0.4562 | 0.7982 |
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+ | 0.3855 | 54.97 | 426 | 0.4640 | 0.8073 |
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+ | 0.4113 | 56.0 | 434 | 0.4474 | 0.8165 |
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+ | 0.4282 | 56.9 | 441 | 0.4540 | 0.7982 |
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+ | 0.4282 | 57.94 | 449 | 0.4450 | 0.8165 |
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+ | 0.4499 | 58.97 | 457 | 0.4497 | 0.8165 |
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+ | 0.4179 | 60.0 | 465 | 0.4400 | 0.8073 |
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+ | 0.4213 | 60.9 | 472 | 0.4392 | 0.8073 |
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+ | 0.4176 | 61.94 | 480 | 0.4325 | 0.8257 |
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+ | 0.4176 | 62.97 | 488 | 0.4296 | 0.8165 |
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+ | 0.4083 | 64.0 | 496 | 0.4388 | 0.8165 |
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+ | 0.3853 | 64.9 | 503 | 0.4392 | 0.8073 |
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+ | 0.3647 | 65.94 | 511 | 0.4349 | 0.8073 |
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+ | 0.3647 | 66.97 | 519 | 0.4344 | 0.8257 |
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+ | 0.3927 | 68.0 | 527 | 0.4348 | 0.8073 |
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+ | 0.3833 | 68.9 | 534 | 0.4352 | 0.8073 |
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+ | 0.3932 | 69.94 | 542 | 0.4294 | 0.8165 |
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+ | 0.4085 | 70.97 | 550 | 0.4276 | 0.8073 |
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+ | 0.4085 | 72.0 | 558 | 0.4232 | 0.8073 |
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+ | 0.4029 | 72.26 | 560 | 0.4359 | 0.8165 |
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  ### Framework versions
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