End of training

README.md

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+---
+library_name: transformers
+language:
+- ru
+license: apache-2.0
+base_model: PekingU/rtdetr_r50vd_coco_o365
+tags:
+- generated_from_trainer
+model-index:
+- name: RT-DETR Russian car plate detection with classification by type
+  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. -->
+
+# RT-DETR Russian car plate detection with classification by type
+
+This model is a fine-tuned version of [PekingU/rtdetr_r50vd_coco_o365](https://huggingface.co/PekingU/rtdetr_r50vd_coco_o365) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 4.1673
+- Map: 0.8829
+- Map 50: 0.9858
+- Map 75: 0.9736
+- Map Car-plates-and-these-types: -1.0
+- Map Large: 0.9689
+- Map Medium: 0.9125
+- Map N P: 0.857
+- Map P P: 0.9087
+- Map Small: 0.696
+- Mar 1: 0.8686
+- Mar 10: 0.9299
+- Mar 100: 0.9357
+- Mar 100 Car-plates-and-these-types: -1.0
+- Mar 100 N P: 0.9169
+- Mar 100 P P: 0.9545
+- Mar Large: 0.9844
+- Mar Medium: 0.958
+- Mar Small: 0.8354
+
+## 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: 32
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 300
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Map    | Map 50 | Map 75 | Map Car-plates-and-these-types | Map Large | Map Medium | Map N P | Map P P | Map Small | Mar 1  | Mar 10 | Mar 100 | Mar 100 Car-plates-and-these-types | Mar 100 N P | Mar 100 P P | Mar Large | Mar Medium | Mar Small |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------------------------------:|:---------:|:----------:|:-------:|:-------:|:---------:|:------:|:------:|:-------:|:----------------------------------:|:-----------:|:-----------:|:---------:|:----------:|:---------:|
+| No log        | 1.0   | 109  | 64.6127         | 0.035  | 0.0558 | 0.0379 | -1.0                           | 0.0039    | 0.0663     | 0.0191  | 0.0508  | 0.0071    | 0.1523 | 0.3009 | 0.3361  | -1.0                               | 0.3179      | 0.3543      | 0.7625    | 0.3788     | 0.1157    |
+| No log        | 2.0   | 218  | 15.4008         | 0.8237 | 0.9418 | 0.9327 | -1.0                           | 0.893     | 0.879      | 0.7945  | 0.8529  | 0.4319    | 0.8203 | 0.8924 | 0.9018  | -1.0                               | 0.8766      | 0.9269      | 0.9656    | 0.9324     | 0.7653    |
+| No log        | 3.0   | 327  | 9.4050          | 0.8439 | 0.9566 | 0.9479 | -1.0                           | 0.9439    | 0.8908     | 0.8158  | 0.872   | 0.5171    | 0.8416 | 0.908  | 0.9144  | -1.0                               | 0.9002      | 0.9286      | 0.9781    | 0.9368     | 0.8051    |
+| No log        | 4.0   | 436  | 7.9164          | 0.8493 | 0.9665 | 0.9543 | -1.0                           | 0.9567    | 0.8903     | 0.8338  | 0.8648  | 0.5581    | 0.8481 | 0.9159 | 0.9267  | -1.0                               | 0.9173      | 0.936       | 0.975     | 0.949      | 0.8185    |
+| 70.2867       | 5.0   | 545  | 6.8177          | 0.8525 | 0.9723 | 0.9602 | -1.0                           | 0.9521    | 0.8918     | 0.8234  | 0.8816  | 0.6025    | 0.8438 | 0.9214 | 0.9279  | -1.0                               | 0.9181      | 0.9378      | 0.975     | 0.9492     | 0.8211    |
+| 70.2867       | 6.0   | 654  | 6.0182          | 0.854  | 0.9744 | 0.9619 | -1.0                           | 0.9574    | 0.8912     | 0.8251  | 0.8829  | 0.6123    | 0.8438 | 0.9176 | 0.927   | -1.0                               | 0.9137      | 0.9403      | 0.9781    | 0.9503     | 0.8163    |
+| 70.2867       | 7.0   | 763  | 5.4024          | 0.8731 | 0.9772 | 0.9667 | -1.0                           | 0.9635    | 0.9113     | 0.8462  | 0.9001  | 0.6376    | 0.8608 | 0.9275 | 0.9336  | -1.0                               | 0.9202      | 0.9471      | 0.9781    | 0.956      | 0.8266    |
+| 70.2867       | 8.0   | 872  | 5.2224          | 0.8726 | 0.9809 | 0.9767 | -1.0                           | 0.9582    | 0.9069     | 0.8487  | 0.8966  | 0.6472    | 0.8625 | 0.9265 | 0.9301  | -1.0                               | 0.9137      | 0.9464      | 0.9875    | 0.9528     | 0.8232    |
+| 70.2867       | 9.0   | 981  | 4.7844          | 0.8679 | 0.9821 | 0.9687 | -1.0                           | 0.9574    | 0.9023     | 0.8451  | 0.8907  | 0.6382    | 0.8606 | 0.9213 | 0.9283  | -1.0                               | 0.9119      | 0.9448      | 0.9844    | 0.952      | 0.8165    |
+| 4.2466        | 10.0  | 1090 | 5.1437          | 0.8729 | 0.9816 | 0.9762 | -1.0                           | 0.9577    | 0.9028     | 0.8448  | 0.901   | 0.6686    | 0.8605 | 0.9296 | 0.9359  | -1.0                               | 0.9203      | 0.9514      | 0.9781    | 0.9567     | 0.8413    |
+| 4.2466        | 11.0  | 1199 | 4.5169          | 0.8858 | 0.9828 | 0.9768 | -1.0                           | 0.9707    | 0.9162     | 0.8628  | 0.9087  | 0.6734    | 0.8695 | 0.9264 | 0.931   | -1.0                               | 0.9121      | 0.95        | 0.9781    | 0.9538     | 0.823     |
+| 4.2466        | 12.0  | 1308 | 4.5858          | 0.8813 | 0.9865 | 0.9744 | -1.0                           | 0.9623    | 0.9126     | 0.8585  | 0.9041  | 0.6815    | 0.8671 | 0.9308 | 0.9355  | -1.0                               | 0.9185      | 0.9526      | 0.9812    | 0.9583     | 0.8308    |
+| 4.2466        | 13.0  | 1417 | 4.5345          | 0.8778 | 0.9843 | 0.9726 | -1.0                           | 0.957     | 0.9101     | 0.8526  | 0.903   | 0.6754    | 0.8628 | 0.9281 | 0.9335  | -1.0                               | 0.9158      | 0.9512      | 0.9812    | 0.9557     | 0.8314    |
+| 3.589         | 14.0  | 1526 | 4.3003          | 0.8885 | 0.9857 | 0.9759 | -1.0                           | 0.9656    | 0.9189     | 0.8642  | 0.9128  | 0.6957    | 0.8724 | 0.9334 | 0.9375  | -1.0                               | 0.9194      | 0.9555      | 0.9875    | 0.959      | 0.8375    |
+| 3.589         | 15.0  | 1635 | 4.3999          | 0.8819 | 0.986  | 0.9741 | -1.0                           | 0.9606    | 0.9118     | 0.8575  | 0.9064  | 0.6892    | 0.8659 | 0.9283 | 0.9336  | -1.0                               | 0.9137      | 0.9534      | 0.9844    | 0.9566     | 0.8245    |
+| 3.589         | 16.0  | 1744 | 4.2719          | 0.8796 | 0.986  | 0.9726 | -1.0                           | 0.9661    | 0.9093     | 0.8543  | 0.905   | 0.6914    | 0.8649 | 0.927  | 0.9313  | -1.0                               | 0.9121      | 0.9505      | 0.9875    | 0.9543     | 0.8266    |
+| 3.589         | 17.0  | 1853 | 4.2497          | 0.8838 | 0.9845 | 0.9733 | -1.0                           | 0.9656    | 0.9141     | 0.8599  | 0.9077  | 0.6997    | 0.8678 | 0.9295 | 0.9352  | -1.0                               | 0.9141      | 0.9562      | 0.9812    | 0.958      | 0.832     |
+| 3.589         | 18.0  | 1962 | 4.2807          | 0.8829 | 0.9855 | 0.9754 | -1.0                           | 0.9673    | 0.9121     | 0.8558  | 0.9099  | 0.6964    | 0.8683 | 0.9286 | 0.9337  | -1.0                               | 0.9126      | 0.9548      | 0.9844    | 0.9555     | 0.8357    |
+| 3.2442        | 19.0  | 2071 | 4.1978          | 0.8835 | 0.9861 | 0.9748 | -1.0                           | 0.9675    | 0.9121     | 0.8559  | 0.911   | 0.6932    | 0.8691 | 0.9272 | 0.9336  | -1.0                               | 0.9134      | 0.9538      | 0.9844    | 0.9557     | 0.8337    |
+| 3.2442        | 20.0  | 2180 | 4.1673          | 0.8829 | 0.9858 | 0.9736 | -1.0                           | 0.9689    | 0.9125     | 0.857   | 0.9087  | 0.696     | 0.8686 | 0.9299 | 0.9357  | -1.0                               | 0.9169      | 0.9545      | 0.9844    | 0.958      | 0.8354    |
+
+
+### Framework versions
+
+- Transformers 4.46.0.dev0
+- Pytorch 2.5.0+cu124
+- Tokenizers 0.20.1

config.json

@@ -0,0 +1,101 @@
+{
+  "_name_or_path": "PekingU/rtdetr_r50vd_coco_o365",
+  "activation_dropout": 0.0,
+  "activation_function": "silu",
+  "anchor_image_size": null,
+  "architectures": [
+    "RTDetrForObjectDetection"
+  ],
+  "attention_dropout": 0.0,
+  "auxiliary_loss": true,
+  "backbone": null,
+  "backbone_config": {
+    "model_type": "rt_detr_resnet",
+    "out_features": [
+      "stage2",
+      "stage3",
+      "stage4"
+    ],
+    "out_indices": [
+      2,
+      3,
+      4
+    ]
+  },
+  "backbone_kwargs": null,
+  "batch_norm_eps": 1e-05,
+  "box_noise_scale": 1.0,
+  "d_model": 256,
+  "decoder_activation_function": "relu",
+  "decoder_attention_heads": 8,
+  "decoder_ffn_dim": 1024,
+  "decoder_in_channels": [
+    256,
+    256,
+    256
+  ],
+  "decoder_layers": 6,
+  "decoder_n_points": 4,
+  "disable_custom_kernels": true,
+  "dropout": 0.0,
+  "encode_proj_layers": [
+    2
+  ],
+  "encoder_activation_function": "gelu",
+  "encoder_attention_heads": 8,
+  "encoder_ffn_dim": 1024,
+  "encoder_hidden_dim": 256,
+  "encoder_in_channels": [
+    512,
+    1024,
+    2048
+  ],
+  "encoder_layers": 1,
+  "eos_coefficient": 0.0001,
+  "eval_size": null,
+  "feat_strides": [
+    8,
+    16,
+    32
+  ],
+  "focal_loss_alpha": 0.75,
+  "focal_loss_gamma": 2.0,
+  "freeze_backbone_batch_norms": true,
+  "hidden_expansion": 1.0,
+  "id2label": {
+    "0": "car-plates-and-these-types",
+    "1": "n_p",
+    "2": "p_p"
+  },
+  "initializer_bias_prior_prob": null,
+  "initializer_range": 0.01,
+  "is_encoder_decoder": true,
+  "label2id": {
+    "car-plates-and-these-types": 0,
+    "n_p": 1,
+    "p_p": 2
+  },
+  "label_noise_ratio": 0.5,
+  "layer_norm_eps": 1e-05,
+  "learn_initial_query": false,
+  "matcher_alpha": 0.25,
+  "matcher_bbox_cost": 5.0,
+  "matcher_class_cost": 2.0,
+  "matcher_gamma": 2.0,
+  "matcher_giou_cost": 2.0,
+  "model_type": "rt_detr",
+  "normalize_before": false,
+  "num_denoising": 100,
+  "num_feature_levels": 3,
+  "num_queries": 300,
+  "positional_encoding_temperature": 10000,
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.0.dev0",
+  "use_focal_loss": true,
+  "use_pretrained_backbone": false,
+  "use_timm_backbone": false,
+  "weight_loss_bbox": 5.0,
+  "weight_loss_giou": 2.0,
+  "weight_loss_vfl": 1.0,
+  "with_box_refine": true
+}

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preprocessor_config.json

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+  "do_rescale": true,
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+  }
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