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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: output |
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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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# output |
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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: 0.9020 |
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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: 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: cosine |
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- lr_scheduler_warmup_steps: 375 |
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- num_epochs: 30 |
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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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| 1.8809 | 1.0 | 250 | 1.6853 | |
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| 1.4938 | 2.0 | 500 | 1.3327 | |
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| 1.3403 | 3.0 | 750 | 1.2940 | |
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| 1.3485 | 4.0 | 1000 | 1.2512 | |
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| 1.2645 | 5.0 | 1250 | 1.2189 | |
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| 1.2061 | 6.0 | 1500 | 1.1517 | |
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| 1.1632 | 7.0 | 1750 | 1.1042 | |
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| 1.179 | 8.0 | 2000 | 1.0796 | |
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| 1.1558 | 9.0 | 2250 | 1.0567 | |
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| 1.1294 | 10.0 | 2500 | 1.0661 | |
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| 1.0644 | 11.0 | 2750 | 1.0214 | |
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| 1.0545 | 12.0 | 3000 | 1.0508 | |
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| 1.0455 | 13.0 | 3250 | 0.9904 | |
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| 1.0242 | 14.0 | 3500 | 0.9863 | |
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| 1.0021 | 15.0 | 3750 | 0.9897 | |
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| 0.9947 | 16.0 | 4000 | 0.9774 | |
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| 0.9456 | 17.0 | 4250 | 0.9485 | |
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| 0.9339 | 18.0 | 4500 | 0.9553 | |
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| 0.9481 | 19.0 | 4750 | 0.9431 | |
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| 0.8992 | 20.0 | 5000 | 0.9348 | |
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| 0.8792 | 21.0 | 5250 | 0.9265 | |
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| 0.8946 | 22.0 | 5500 | 0.9271 | |
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| 0.8913 | 23.0 | 5750 | 0.9249 | |
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| 0.8813 | 24.0 | 6000 | 0.9072 | |
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| 0.885 | 25.0 | 6250 | 0.9115 | |
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| 0.8477 | 26.0 | 6500 | 0.9091 | |
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| 0.8792 | 27.0 | 6750 | 0.9045 | |
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| 0.8816 | 28.0 | 7000 | 0.9034 | |
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| 0.8633 | 29.0 | 7250 | 0.9005 | |
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| 0.8921 | 30.0 | 7500 | 0.9102 | |
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### Framework versions |
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- Transformers 4.51.3 |
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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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