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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-dc5 |
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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-dc5-fashionpedia-finetuned |
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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-dc5-fashionpedia-finetuned |
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This model is a fine-tuned version of [facebook/detr-resnet-50-dc5](https://huggingface.co/facebook/detr-resnet-50-dc5) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.2904 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- training_steps: 1000 |
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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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| 4.7281 | 0.0438 | 50 | 4.3705 | |
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| 3.9353 | 0.0876 | 100 | 4.0499 | |
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| 4.5369 | 0.1315 | 150 | 3.8890 | |
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| 3.9156 | 0.1753 | 200 | 3.7630 | |
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| 3.6006 | 0.2191 | 250 | 3.6861 | |
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| 3.6562 | 0.2629 | 300 | 3.6110 | |
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| 3.7636 | 0.3067 | 350 | 3.5906 | |
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| 4.0293 | 0.3506 | 400 | 3.5405 | |
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| 3.533 | 0.3944 | 450 | 3.4906 | |
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| 3.1302 | 0.4382 | 500 | 3.4249 | |
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| 3.8257 | 0.4820 | 550 | 3.3910 | |
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| 2.9622 | 0.5259 | 600 | 3.3622 | |
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| 3.9213 | 0.5697 | 650 | 3.3310 | |
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| 4.4062 | 0.6135 | 700 | 3.3303 | |
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| 4.3076 | 0.6573 | 750 | 3.3105 | |
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| 4.0868 | 0.7011 | 800 | 3.3040 | |
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| 4.0639 | 0.7450 | 850 | 3.3076 | |
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| 4.7454 | 0.7888 | 900 | 3.2996 | |
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| 4.3044 | 0.8326 | 950 | 3.2935 | |
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| 3.9519 | 0.8764 | 1000 | 3.2904 | |
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### Framework versions |
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- Transformers 4.51.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
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