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swiftformer-xs-DMAE

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End of training

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Files changed (9) hide show
  1. README.md +36 -36
  2. all_results.json +8 -8
  3. eval_results.json +4 -4
  4. model.safetensors +1 -1
  5. runs/Dec02_10-27-56_DESKTOP-SKBE9FB/events.out.tfevents.1733156877.DESKTOP-SKBE9FB.17416.0 +3 -0
  6. runs/Dec02_10-27-56_DESKTOP-SKBE9FB/events.out.tfevents.1733157009.DESKTOP-SKBE9FB.17416.1 +3 -0
  7. train_results.json +4 -4
  8. trainer_state.json +156 -156
  9. training_args.bin +1 -1
README.md CHANGED
@@ -31,7 +31,7 @@ should probably proofread and complete it, then remove this comment. -->
31
 
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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: 113.8883
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  - Accuracy: 0.1087
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  ## Model description
@@ -65,41 +65,41 @@ The following hyperparameters were used during training:
65
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 0.86 | 3 | 113.8883 | 0.1087 |
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- | No log | 2.0 | 7 | 113.8868 | 0.1087 |
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- | 114.1606 | 2.86 | 10 | 113.8851 | 0.1087 |
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- | 114.1606 | 4.0 | 14 | 113.8846 | 0.1087 |
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- | 114.1606 | 4.86 | 17 | 113.8832 | 0.1087 |
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- | 113.5172 | 6.0 | 21 | 113.8808 | 0.1087 |
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- | 113.5172 | 6.86 | 24 | 113.8795 | 0.1087 |
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- | 113.5172 | 8.0 | 28 | 113.8794 | 0.1087 |
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- | 111.7557 | 8.86 | 31 | 113.8766 | 0.1087 |
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- | 111.7557 | 10.0 | 35 | 113.8747 | 0.1087 |
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- | 114.0835 | 20.86 | 73 | 113.8469 | 0.1087 |
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- | 114.5528 | 24.0 | 84 | 113.8341 | 0.1087 |
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- | 114.5528 | 24.86 | 87 | 113.8315 | 0.1087 |
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- | 114.5432 | 26.0 | 91 | 113.8268 | 0.1087 |
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- | 114.0925 | 34.29 | 120 | 113.8146 | 0.1087 |
103
 
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  ### Framework versions
 
31
 
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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.
33
  It achieves the following results on the evaluation set:
34
+ - Loss: 113.8668
35
  - Accuracy: 0.1087
36
 
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  ## Model description
 
65
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.86 | 3 | 113.8668 | 0.1087 |
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+ | No log | 2.0 | 7 | 113.8652 | 0.1087 |
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+ | 114.139 | 2.86 | 10 | 113.8636 | 0.1087 |
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+ | 114.139 | 4.0 | 14 | 113.8630 | 0.1087 |
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+ | 114.139 | 4.86 | 17 | 113.8617 | 0.1087 |
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+ | 111.7345 | 10.0 | 35 | 113.8531 | 0.1087 |
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+ | 111.7345 | 10.86 | 38 | 113.8520 | 0.1087 |
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+ | 115.9214 | 12.0 | 42 | 113.8497 | 0.1087 |
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+ | 115.9214 | 12.86 | 45 | 113.8484 | 0.1087 |
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+ | 115.9214 | 14.0 | 49 | 113.8455 | 0.1087 |
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+ | 112.3215 | 14.86 | 52 | 113.8392 | 0.1087 |
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+ | 112.3215 | 16.0 | 56 | 113.8351 | 0.1087 |
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+ | 112.3215 | 16.86 | 59 | 113.8354 | 0.1087 |
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+ | 113.1908 | 18.0 | 63 | 113.8316 | 0.1087 |
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+ | 113.1908 | 18.86 | 66 | 113.8295 | 0.1087 |
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+ | 114.062 | 20.0 | 70 | 113.8284 | 0.1087 |
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+ | 114.062 | 20.86 | 73 | 113.8253 | 0.1087 |
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+ | 114.062 | 22.0 | 77 | 113.8235 | 0.1087 |
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+ | 114.5312 | 22.86 | 80 | 113.8207 | 0.1087 |
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+ | 114.5312 | 24.0 | 84 | 113.8126 | 0.1087 |
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+ | 114.5312 | 24.86 | 87 | 113.8100 | 0.1087 |
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+ | 114.5216 | 26.0 | 91 | 113.8053 | 0.1087 |
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+ | 114.5216 | 26.86 | 94 | 113.8032 | 0.1087 |
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+ | 114.5216 | 28.0 | 98 | 113.8035 | 0.1087 |
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+ | 112.7612 | 28.86 | 101 | 113.7992 | 0.1087 |
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+ | 112.7612 | 30.0 | 105 | 113.7939 | 0.1087 |
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+ | 112.7612 | 30.86 | 108 | 113.7967 | 0.1087 |
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+ | 114.2748 | 32.0 | 112 | 113.7973 | 0.1087 |
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+ | 114.2748 | 32.86 | 115 | 113.7971 | 0.1087 |
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+ | 114.2748 | 34.0 | 119 | 113.7908 | 0.1087 |
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+ | 114.0708 | 34.29 | 120 | 113.7932 | 0.1087 |
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  ### Framework versions
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