upload trashify object detection model with data augmentation
Browse files- README.md +83 -0
- config.json +73 -0
- model.safetensors +3 -0
- preprocessor_config.json +26 -0
- training_args.bin +3 -0
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: microsoft/conditional-detr-resnet-50
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tags:
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- generated_from_trainer
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model-index:
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- name: detr_finetuned_trashify_box_detector_with_data_aug
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results: []
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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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# detr_finetuned_trashify_box_detector_with_data_aug
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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.
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It achieves the following results on the evaluation set:
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- Loss: 1.0749
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 16
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- eval_batch_size: 16
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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: linear
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- num_epochs: 25
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 36.0329 | 1.0 | 50 | 3.4510 |
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| 2.8564 | 2.0 | 100 | 2.2827 |
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| 2.3323 | 3.0 | 150 | 2.1028 |
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| 2.1202 | 4.0 | 200 | 1.8915 |
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| 1.9452 | 5.0 | 250 | 1.6696 |
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| 1.7582 | 6.0 | 300 | 1.5181 |
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| 1.6291 | 7.0 | 350 | 1.4310 |
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| 1.5394 | 8.0 | 400 | 1.3669 |
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| 1.4751 | 9.0 | 450 | 1.3164 |
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| 1.3906 | 10.0 | 500 | 1.2860 |
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| 1.394 | 11.0 | 550 | 1.2915 |
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| 1.338 | 12.0 | 600 | 1.2461 |
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| 1.3071 | 13.0 | 650 | 1.2300 |
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| 1.2772 | 14.0 | 700 | 1.2059 |
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| 1.2363 | 15.0 | 750 | 1.1639 |
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| 1.2213 | 16.0 | 800 | 1.1547 |
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| 1.1372 | 17.0 | 850 | 1.1213 |
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| 1.1423 | 18.0 | 900 | 1.1322 |
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| 1.0991 | 19.0 | 950 | 1.1069 |
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| 1.1041 | 20.0 | 1000 | 1.1001 |
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| 1.0921 | 21.0 | 1050 | 1.0869 |
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| 1.063 | 22.0 | 1100 | 1.0760 |
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| 1.0561 | 23.0 | 1150 | 1.0775 |
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| 1.0373 | 24.0 | 1200 | 1.0799 |
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| 1.0325 | 25.0 | 1250 | 1.0749 |
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### Framework versions
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- Transformers 4.45.0.dev0
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- Pytorch 2.4.0+cu124
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "microsoft/conditional-detr-resnet-50",
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"activation_dropout": 0.0,
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"activation_function": "relu",
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"architectures": [
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"ConditionalDetrForObjectDetection"
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],
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"attention_dropout": 0.0,
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"auxiliary_loss": false,
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"backbone": "resnet50",
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"backbone_config": null,
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"backbone_kwargs": {
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"in_chans": 3,
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"out_indices": [
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1,
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2,
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3,
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4
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]
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},
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"bbox_cost": 5,
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"bbox_loss_coefficient": 5,
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"class_cost": 2,
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"cls_loss_coefficient": 2,
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"d_model": 256,
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"decoder_attention_heads": 8,
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"decoder_ffn_dim": 2048,
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"decoder_layerdrop": 0.0,
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"decoder_layers": 6,
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"dice_loss_coefficient": 1,
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"dilation": false,
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"dropout": 0.1,
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"encoder_attention_heads": 8,
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"encoder_ffn_dim": 2048,
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"encoder_layerdrop": 0.0,
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"encoder_layers": 6,
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"focal_alpha": 0.25,
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"giou_cost": 2,
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"giou_loss_coefficient": 2,
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"id2label": {
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"0": "bin",
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"1": "hand",
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"2": "not_bin",
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"3": "not_hand",
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"4": "not_trash",
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"5": "trash",
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"6": "trash_arm"
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},
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"init_std": 0.02,
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"init_xavier_std": 1.0,
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"is_encoder_decoder": true,
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"label2id": {
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"bin": 0,
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"hand": 1,
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"not_bin": 2,
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"not_hand": 3,
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"not_trash": 4,
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"trash": 5,
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"trash_arm": 6
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},
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"mask_loss_coefficient": 1,
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"max_position_embeddings": 1024,
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"model_type": "conditional_detr",
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"num_channels": 3,
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"num_hidden_layers": 6,
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"num_queries": 300,
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"position_embedding_type": "sine",
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"scale_embedding": false,
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"torch_dtype": "float32",
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"transformers_version": "4.45.0.dev0",
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"use_pretrained_backbone": true,
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"use_timm_backbone": true
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:fe0684c55e44bd02e61048c6a12912d159e5370547f518c354fcae901301532e
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size 174081852
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preprocessor_config.json
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{
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"do_convert_annotations": true,
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"do_normalize": true,
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"do_pad": true,
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"do_rescale": true,
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"do_resize": true,
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"format": "coco_detection",
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"image_mean": [
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0.485,
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0.456,
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0.406
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],
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"image_processor_type": "ConditionalDetrImageProcessor",
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"image_std": [
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0.229,
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0.224,
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0.225
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],
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"pad_size": null,
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"longest_edge": 640,
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"shortest_edge": 640
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}
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:f66c68bea1d5455cab041a87da03b15d66801c6130700b0c1ebd0179639024df
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size 5240
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