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Yolo_temp

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Training in progress, epoch 1

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  1. README.md +102 -0
  2. config.json +40 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +26 -0
  5. runs/Sep04_17-10-20_A41103/events.out.tfevents.1725437423.A41103.26372.0 +3 -0
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: hustvl/yolos-tiny
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: Yolo_temp
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+ results: []
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+ ---
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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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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Yolo_temp
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+
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+ This model is a fine-tuned version of [hustvl/yolos-tiny](https://huggingface.co/hustvl/yolos-tiny) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6429
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+ - Map: 0.2495
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+ - Map 50: 0.553
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+ - Map 75: 0.1318
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+ - Map Small: -1.0
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+ - Map Medium: 0.3503
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+ - Map Large: -1.0
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+ - Mar 1: 0.45
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+ - Mar 10: 0.64
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+ - Mar 100: 0.66
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+ - Mar Small: -1.0
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+ - Mar Medium: 0.66
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+ - Mar Large: -1.0
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+ - Map Background : -1.0
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+ - Mar 100 Background : -1.0
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+ - Map Score: 0.2495
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+ - Mar 100 Score: 0.66
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - num_epochs: 30
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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 Background | Mar 100 Background | Map Score | Mar 100 Score |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:-----:|:------:|:-------:|:---------:|:----------:|:---------:|:----------------:|:--------------------:|:---------:|:-------------:|
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+ | No log | 1.0 | 9 | 3.3868 | 0.0003 | 0.0013 | 0.0 | -1.0 | 0.0009 | -1.0 | 0.0 | 0.02 | 0.02 | -1.0 | 0.02 | -1.0 | -1.0 | -1.0 | 0.0003 | 0.02 |
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+ | No log | 2.0 | 18 | 2.0202 | 0.0061 | 0.0613 | 0.0 | -1.0 | 0.0128 | -1.0 | 0.0 | 0.02 | 0.03 | -1.0 | 0.03 | -1.0 | -1.0 | -1.0 | 0.0061 | 0.03 |
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+ | No log | 3.0 | 27 | 1.3924 | 0.0243 | 0.1074 | 0.0 | -1.0 | 0.0537 | -1.0 | 0.04 | 0.16 | 0.24 | -1.0 | 0.24 | -1.0 | -1.0 | -1.0 | 0.0243 | 0.24 |
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+ | No log | 4.0 | 36 | 1.0148 | 0.1265 | 0.4427 | 0.0227 | -1.0 | 0.1956 | -1.0 | 0.16 | 0.41 | 0.47 | -1.0 | 0.47 | -1.0 | -1.0 | -1.0 | 0.1265 | 0.47 |
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+ | No log | 5.0 | 45 | 0.8707 | 0.1387 | 0.3888 | 0.0565 | -1.0 | 0.2082 | -1.0 | 0.23 | 0.53 | 0.56 | -1.0 | 0.56 | -1.0 | -1.0 | -1.0 | 0.1387 | 0.56 |
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+ | No log | 6.0 | 54 | 1.0714 | 0.0534 | 0.1731 | 0.0042 | -1.0 | 0.0797 | -1.0 | 0.04 | 0.39 | 0.4 | -1.0 | 0.4 | -1.0 | -1.0 | -1.0 | 0.0534 | 0.4 |
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+ | No log | 7.0 | 63 | 0.8522 | 0.2023 | 0.4156 | 0.2261 | -1.0 | 0.2423 | -1.0 | 0.33 | 0.53 | 0.53 | -1.0 | 0.53 | -1.0 | -1.0 | -1.0 | 0.2023 | 0.53 |
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+ | No log | 8.0 | 72 | 0.8514 | 0.0796 | 0.1838 | 0.077 | -1.0 | 0.2324 | -1.0 | 0.15 | 0.53 | 0.54 | -1.0 | 0.54 | -1.0 | -1.0 | -1.0 | 0.0796 | 0.54 |
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+ | No log | 9.0 | 81 | 0.8325 | 0.0791 | 0.1867 | 0.0402 | -1.0 | 0.1144 | -1.0 | 0.16 | 0.54 | 0.57 | -1.0 | 0.57 | -1.0 | -1.0 | -1.0 | 0.0791 | 0.57 |
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+ | No log | 10.0 | 90 | 0.6108 | 0.138 | 0.2665 | 0.1586 | -1.0 | 0.303 | -1.0 | 0.25 | 0.7 | 0.72 | -1.0 | 0.72 | -1.0 | -1.0 | -1.0 | 0.138 | 0.72 |
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+ | No log | 11.0 | 99 | 0.5912 | 0.2034 | 0.3462 | 0.1951 | -1.0 | 0.2395 | -1.0 | 0.51 | 0.7 | 0.72 | -1.0 | 0.72 | -1.0 | -1.0 | -1.0 | 0.2034 | 0.72 |
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+ | No log | 12.0 | 108 | 0.6538 | 0.2105 | 0.3835 | 0.2217 | -1.0 | 0.3013 | -1.0 | 0.39 | 0.68 | 0.68 | -1.0 | 0.68 | -1.0 | -1.0 | -1.0 | 0.2105 | 0.68 |
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+ | No log | 13.0 | 117 | 0.5392 | 0.2524 | 0.397 | 0.2813 | -1.0 | 0.2997 | -1.0 | 0.47 | 0.74 | 0.75 | -1.0 | 0.75 | -1.0 | -1.0 | -1.0 | 0.2524 | 0.75 |
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+ | No log | 14.0 | 126 | 0.6936 | 0.2087 | 0.4142 | 0.1474 | -1.0 | 0.248 | -1.0 | 0.37 | 0.63 | 0.63 | -1.0 | 0.63 | -1.0 | -1.0 | -1.0 | 0.2087 | 0.63 |
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+ | No log | 15.0 | 135 | 0.6347 | 0.2024 | 0.4126 | 0.1546 | -1.0 | 0.2879 | -1.0 | 0.35 | 0.62 | 0.68 | -1.0 | 0.68 | -1.0 | -1.0 | -1.0 | 0.2024 | 0.68 |
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+ | No log | 16.0 | 144 | 0.6651 | 0.2255 | 0.4622 | 0.1581 | -1.0 | 0.2797 | -1.0 | 0.42 | 0.61 | 0.64 | -1.0 | 0.64 | -1.0 | -1.0 | -1.0 | 0.2255 | 0.64 |
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+ | No log | 17.0 | 153 | 0.7808 | 0.1881 | 0.5016 | 0.0459 | -1.0 | 0.3059 | -1.0 | 0.36 | 0.53 | 0.54 | -1.0 | 0.54 | -1.0 | -1.0 | -1.0 | 0.1881 | 0.54 |
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+ | No log | 18.0 | 162 | 0.6863 | 0.2272 | 0.4952 | 0.1514 | -1.0 | 0.3529 | -1.0 | 0.43 | 0.6 | 0.61 | -1.0 | 0.61 | -1.0 | -1.0 | -1.0 | 0.2272 | 0.61 |
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+ | No log | 19.0 | 171 | 0.7358 | 0.2335 | 0.5157 | 0.0908 | -1.0 | 0.2779 | -1.0 | 0.4 | 0.58 | 0.61 | -1.0 | 0.61 | -1.0 | -1.0 | -1.0 | 0.2335 | 0.61 |
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+ | No log | 20.0 | 180 | 0.6321 | 0.2591 | 0.5315 | 0.1592 | -1.0 | 0.3527 | -1.0 | 0.47 | 0.65 | 0.67 | -1.0 | 0.67 | -1.0 | -1.0 | -1.0 | 0.2591 | 0.67 |
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+ | No log | 21.0 | 189 | 0.7105 | 0.2244 | 0.52 | 0.1119 | -1.0 | 0.2886 | -1.0 | 0.41 | 0.61 | 0.64 | -1.0 | 0.64 | -1.0 | -1.0 | -1.0 | 0.2244 | 0.64 |
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+ | No log | 22.0 | 198 | 0.6395 | 0.2448 | 0.5329 | 0.1287 | -1.0 | 0.3527 | -1.0 | 0.45 | 0.66 | 0.67 | -1.0 | 0.67 | -1.0 | -1.0 | -1.0 | 0.2448 | 0.67 |
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+ | No log | 23.0 | 207 | 0.6352 | 0.2474 | 0.5273 | 0.2112 | -1.0 | 0.3253 | -1.0 | 0.47 | 0.66 | 0.68 | -1.0 | 0.68 | -1.0 | -1.0 | -1.0 | 0.2474 | 0.68 |
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+ | No log | 24.0 | 216 | 0.6532 | 0.242 | 0.5442 | 0.115 | -1.0 | 0.342 | -1.0 | 0.43 | 0.63 | 0.66 | -1.0 | 0.66 | -1.0 | -1.0 | -1.0 | 0.242 | 0.66 |
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+ | No log | 25.0 | 225 | 0.6458 | 0.249 | 0.548 | 0.1336 | -1.0 | 0.3561 | -1.0 | 0.44 | 0.64 | 0.67 | -1.0 | 0.67 | -1.0 | -1.0 | -1.0 | 0.249 | 0.67 |
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+ | No log | 26.0 | 234 | 0.6434 | 0.2553 | 0.5517 | 0.1729 | -1.0 | 0.3663 | -1.0 | 0.46 | 0.67 | 0.68 | -1.0 | 0.68 | -1.0 | -1.0 | -1.0 | 0.2553 | 0.68 |
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+ | No log | 27.0 | 243 | 0.6437 | 0.2493 | 0.553 | 0.1318 | -1.0 | 0.3494 | -1.0 | 0.44 | 0.64 | 0.66 | -1.0 | 0.66 | -1.0 | -1.0 | -1.0 | 0.2493 | 0.66 |
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+ | No log | 28.0 | 252 | 0.6402 | 0.2495 | 0.553 | 0.1318 | -1.0 | 0.3503 | -1.0 | 0.45 | 0.64 | 0.66 | -1.0 | 0.66 | -1.0 | -1.0 | -1.0 | 0.2495 | 0.66 |
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+ | No log | 29.0 | 261 | 0.6423 | 0.2495 | 0.553 | 0.1321 | -1.0 | 0.3504 | -1.0 | 0.46 | 0.64 | 0.66 | -1.0 | 0.66 | -1.0 | -1.0 | -1.0 | 0.2495 | 0.66 |
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+ | No log | 30.0 | 270 | 0.6429 | 0.2495 | 0.553 | 0.1318 | -1.0 | 0.3503 | -1.0 | 0.45 | 0.64 | 0.66 | -1.0 | 0.66 | -1.0 | -1.0 | -1.0 | 0.2495 | 0.66 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ "num_detection_tokens": 100,
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+ "use_mid_position_embeddings": false
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