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rtdetr-r50-cppe5-finetune

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  1. README.md +38 -1
  2. model.safetensors +1 -1
  3. runs/Jun11_19-01-25_b3d85beef6c6/events.out.tfevents.1749668494.b3d85beef6c6.19.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -15,6 +15,32 @@ should probably proofread and complete it, then remove this comment. -->
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  # rtdetr-r50-cppe5-finetune
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  This model is a fine-tuned version of [hungnguyen2k4/rtdetr-r50-fruits-finetune](https://huggingface.co/hungnguyen2k4/rtdetr-r50-fruits-finetune) on an unknown dataset.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Model description
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@@ -40,7 +66,18 @@ The following hyperparameters were used during training:
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 300
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- - num_epochs: 20
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  # rtdetr-r50-cppe5-finetune
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  This model is a fine-tuned version of [hungnguyen2k4/rtdetr-r50-fruits-finetune](https://huggingface.co/hungnguyen2k4/rtdetr-r50-fruits-finetune) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 10.2690
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+ - Map: 0.5625
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+ - Map 50: 0.6875
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+ - Map 75: 0.5839
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+ - Map Small: 0.2457
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+ - Map Medium: 0.5338
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+ - Map Large: 0.7163
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+ - Mar 1: 0.2862
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+ - Mar 10: 0.6012
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+ - Mar 100: 0.6875
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+ - Mar Small: 0.3606
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+ - Mar Medium: 0.6517
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+ - Mar Large: 0.8526
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+ - Map Apple: 0.5267
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+ - Mar 100 Apple: 0.6703
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+ - Map Banana: 0.5716
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+ - Mar 100 Banana: 0.728
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+ - Map Grapes: 0.4784
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+ - Mar 100 Grapes: 0.5725
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+ - Map Orange: 0.4928
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+ - Mar 100 Orange: 0.611
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+ - Map Pineapple: 0.5979
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+ - Mar 100 Pineapple: 0.7181
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+ - Map Watermelon: 0.7077
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+ - Mar 100 Watermelon: 0.8253
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  ## Model description
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 300
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Apple | Mar 100 Apple | Map Banana | Mar 100 Banana | Map Grapes | Mar 100 Grapes | Map Orange | Mar 100 Orange | Map Pineapple | Mar 100 Pineapple | Map Watermelon | Mar 100 Watermelon |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:---------:|:-------------:|:----------:|:--------------:|:----------:|:--------------:|:----------:|:--------------:|:-------------:|:-----------------:|:--------------:|:------------------:|
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+ | 8.3443 | 1.0 | 750 | 10.1464 | 0.5536 | 0.678 | 0.5795 | 0.252 | 0.5322 | 0.7006 | 0.2857 | 0.6109 | 0.7115 | 0.3705 | 0.6841 | 0.8718 | 0.5243 | 0.6875 | 0.5532 | 0.7416 | 0.4845 | 0.6026 | 0.5187 | 0.6506 | 0.5935 | 0.7558 | 0.6474 | 0.831 |
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+ | 8.585 | 2.0 | 1500 | 10.7682 | 0.5491 | 0.6692 | 0.5745 | 0.2354 | 0.5262 | 0.7017 | 0.2807 | 0.5986 | 0.6917 | 0.3547 | 0.6558 | 0.8609 | 0.5213 | 0.6823 | 0.5466 | 0.7152 | 0.4704 | 0.5735 | 0.4877 | 0.6173 | 0.5865 | 0.7275 | 0.6821 | 0.8341 |
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+ | 8.3452 | 3.0 | 2250 | 10.2876 | 0.5573 | 0.6809 | 0.5787 | 0.2559 | 0.5387 | 0.7033 | 0.2828 | 0.6037 | 0.6905 | 0.3755 | 0.656 | 0.8498 | 0.5161 | 0.6791 | 0.5681 | 0.736 | 0.4935 | 0.5882 | 0.5031 | 0.6283 | 0.5795 | 0.6877 | 0.6832 | 0.8236 |
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+ | 8.0157 | 4.0 | 3000 | 10.3314 | 0.5574 | 0.6809 | 0.5796 | 0.2721 | 0.5321 | 0.7041 | 0.2828 | 0.6024 | 0.6864 | 0.3688 | 0.646 | 0.8524 | 0.5279 | 0.6705 | 0.562 | 0.7246 | 0.4804 | 0.5767 | 0.4949 | 0.6113 | 0.5887 | 0.7199 | 0.6903 | 0.8153 |
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+ | 7.7933 | 5.0 | 3750 | 10.2690 | 0.5625 | 0.6875 | 0.5839 | 0.2457 | 0.5338 | 0.7163 | 0.2862 | 0.6012 | 0.6875 | 0.3606 | 0.6517 | 0.8526 | 0.5267 | 0.6703 | 0.5716 | 0.728 | 0.4784 | 0.5725 | 0.4928 | 0.611 | 0.5979 | 0.7181 | 0.7077 | 0.8253 |
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+
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  ### Framework versions
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