End of training

README.md

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+---
+license: apache-2.0
+base_model: microsoft/conditional-detr-resnet-50
+tags:
+- generated_from_trainer
+model-index:
+- name: msoft_detr_finetuned_cppe5_4
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# msoft_detr_finetuned_cppe5_4
+
+This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.2977
+- Map: 0.021
+- Map 50: 0.0499
+- Map 75: 0.0154
+- Map Small: 0.0068
+- Map Medium: 0.0134
+- Map Large: 0.0527
+- Mar 1: 0.0707
+- Mar 10: 0.1568
+- Mar 100: 0.2057
+- Mar Small: 0.0544
+- Mar Medium: 0.1672
+- Mar Large: 0.2741
+- Map Coverall: 0.06
+- Mar 100 Coverall: 0.5324
+- Map Face Shield: 0.0055
+- Mar 100 Face Shield: 0.0688
+- Map Gloves: 0.0015
+- Mar 100 Gloves: 0.0946
+- Map Goggles: 0.0083
+- Mar 100 Goggles: 0.0639
+- Map Mask: 0.03
+- Mar 100 Mask: 0.2691
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 7
+
+### Training results
+
+| 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 Coverall | Mar 100 Coverall | Map Face Shield | Mar 100 Face Shield | Map Gloves | Mar 100 Gloves | Map Goggles | Mar 100 Goggles | Map Mask | Mar 100 Mask |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:---------------:|:-------------------:|:----------:|:--------------:|:-----------:|:---------------:|:--------:|:------------:|
+| No log        | 1.0   | 32   | 3.7102          | 0.0005 | 0.0021 | 0.0003 | 0.0001    | 0.0004     | 0.0013    | 0.0026 | 0.0261 | 0.0464  | 0.0019    | 0.0354     | 0.0536    | 0.0016       | 0.1713           | 0.0             | 0.0                 | 0.0001     | 0.0123         | 0.0         | 0.0111          | 0.0008   | 0.0375       |
+| No log        | 2.0   | 64   | 2.7691          | 0.0051 | 0.0161 | 0.0015 | 0.0023    | 0.0065     | 0.0113    | 0.0115 | 0.0494 | 0.0884  | 0.0324    | 0.0666     | 0.1259    | 0.0052       | 0.2228           | 0.0             | 0.0                 | 0.0001     | 0.0438         | 0.0007      | 0.0194          | 0.0194   | 0.1559       |
+| No log        | 3.0   | 96   | 2.5735          | 0.0178 | 0.0407 | 0.0149 | 0.0033    | 0.0102     | 0.0334    | 0.0415 | 0.1076 | 0.1578  | 0.0249    | 0.1105     | 0.2077    | 0.0637       | 0.539            | 0.0             | 0.0                 | 0.0002     | 0.0446         | 0.0028      | 0.0222          | 0.0222   | 0.1831       |
+| No log        | 4.0   | 128  | 2.5173          | 0.0246 | 0.0528 | 0.0225 | 0.0048    | 0.0136     | 0.0308    | 0.0557 | 0.1141 | 0.1519  | 0.027     | 0.1288     | 0.2036    | 0.0974       | 0.5074           | 0.0             | 0.0                 | 0.0004     | 0.0692         | 0.0         | 0.0             | 0.0254   | 0.1831       |
+| No log        | 5.0   | 160  | 2.3440          | 0.0167 | 0.0413 | 0.0111 | 0.0066    | 0.0106     | 0.0438    | 0.0517 | 0.1312 | 0.183   | 0.0472    | 0.1398     | 0.2513    | 0.0437       | 0.5022           | 0.0029          | 0.0312              | 0.0009     | 0.0877         | 0.0074      | 0.0528          | 0.0287   | 0.2412       |
+| No log        | 6.0   | 192  | 2.3166          | 0.0203 | 0.0471 | 0.0156 | 0.0064    | 0.0131     | 0.05      | 0.0655 | 0.1514 | 0.2036  | 0.0635    | 0.1626     | 0.2709    | 0.059        | 0.5346           | 0.0039          | 0.0521              | 0.0014     | 0.1015         | 0.0085      | 0.0722          | 0.0286   | 0.2574       |
+| No log        | 7.0   | 224  | 2.2977          | 0.021  | 0.0499 | 0.0154 | 0.0068    | 0.0134     | 0.0527    | 0.0707 | 0.1568 | 0.2057  | 0.0544    | 0.1672     | 0.2741    | 0.06         | 0.5324           | 0.0055          | 0.0688              | 0.0015     | 0.0946         | 0.0083      | 0.0639          | 0.03     | 0.2691       |
+
+
+### Framework versions
+
+- Transformers 4.44.0
+- Pytorch 2.5.0+cu124
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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