KevinLe commited on
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End of training

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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: 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_output
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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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+ # detr_output
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+
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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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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9322
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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: 64
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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: 10
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.9858 | 6.37 | 1000 | 0.9322 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.15.2
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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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+ ],
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+ "downsample_in_first_stage": false,
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+ "early_stopping": false,
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+ "embedding_size": 64,
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+ "hidden_act": "relu",
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+ "hidden_sizes": [
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+ ],
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+ "id2label": {
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+ "model_type": "resnet",
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+ "1": "Clothing",
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+ "2": "Shoes",
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+ "3": "Bags",
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+ "4": "Accessories"
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+ "mask_loss_coefficient": 1,
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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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+ "torch_dtype": "float32",
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+ "transformers_version": "4.38.2",
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+ "use_pretrained_backbone": null,
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+ "use_timm_backbone": false
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