detr-resnet-50-finetuned-boat-dataset 30 epoch
Browse files- README.md +49 -0
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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: facebook/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-resnet-50-finetuned-30-epochs-boat-dataset
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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-resnet-50-finetuned-30-epochs-boat-dataset
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This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on an unknown dataset.
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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: 1e-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: linear
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- num_epochs: 30
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.1+cu121
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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": "facebook/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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"DetrForObjectDetection"
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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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},
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"bbox_cost": 5,
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"bbox_loss_coefficient": 5,
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"class_cost": 1,
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"classifier_dropout": 0.0,
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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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"eos_coefficient": 0.1,
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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": "BallonBoat",
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"1": "BigBoat",
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"2": "Boat",
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"3": "JetSki",
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"4": "Katamaran",
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"5": "SailBoat",
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"6": "SmallBoat",
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"7": "SpeedBoat",
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"8": "WAM_V",
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"9": "container_ship",
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"10": "TugShip",
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"11": "yacht",
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"12": "blueboat"
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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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"BallonBoat": 0,
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"BigBoat": 1,
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"Boat": 2,
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"JetSki": 3,
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"Katamaran": 4,
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"SailBoat": 5,
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"SmallBoat": 6,
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"SpeedBoat": 7,
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"TugShip": 10,
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"WAM_V": 8,
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"blueboat": 12,
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"container_ship": 9,
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"yacht": 11
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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": "detr",
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"num_channels": 3,
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"num_hidden_layers": 6,
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"num_queries": 100,
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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": "4.44.2",
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"use_pretrained_backbone": true,
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"use_timm_backbone": true
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}
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