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--- |
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license: apache-2.0 |
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library_name: transformers |
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tags: |
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- lam |
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- newspapers |
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datasets: |
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- biglam/loc_beyond_words |
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pipeline_tag: object-detection |
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base_model: facebook/detr-resnet-50 |
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model-index: |
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- name: detr-resnet-50_fine_tuned_loc-2023 |
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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_fine_tuned_loc-2023 |
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This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on the loc_beyond_words dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8784 |
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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: 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: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 3.731 | 0.16 | 50 | 2.6356 | |
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| 2.4875 | 0.31 | 100 | 2.2348 | |
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| 2.1786 | 0.47 | 150 | 2.1148 | |
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| 1.9845 | 0.62 | 200 | 1.8847 | |
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| 1.8507 | 0.78 | 250 | 1.8331 | |
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| 1.6813 | 0.94 | 300 | 1.5620 | |
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| 1.5613 | 1.09 | 350 | 1.5898 | |
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| 1.4966 | 1.25 | 400 | 1.4161 | |
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| 1.4831 | 1.41 | 450 | 1.4831 | |
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| 1.4587 | 1.56 | 500 | 1.3218 | |
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| 1.433 | 1.72 | 550 | 1.3529 | |
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| 1.33 | 1.88 | 600 | 1.2453 | |
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| 1.2842 | 2.03 | 650 | 1.2956 | |
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| 1.2807 | 2.19 | 700 | 1.1993 | |
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| 1.1767 | 2.34 | 750 | 1.1557 | |
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| 1.2134 | 2.5 | 800 | 1.1393 | |
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| 1.1897 | 2.66 | 850 | 1.2016 | |
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| 1.1784 | 2.81 | 900 | 1.1235 | |
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| 1.2016 | 2.97 | 950 | 1.1378 | |
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| 1.06 | 3.12 | 1000 | 1.0803 | |
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| 1.1124 | 3.28 | 1050 | 1.1145 | |
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| 1.1191 | 3.44 | 1100 | 1.0523 | |
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| 1.0819 | 3.59 | 1150 | 1.0165 | |
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| 1.1196 | 3.75 | 1200 | 1.0349 | |
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| 1.0534 | 3.91 | 1250 | 1.0441 | |
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| 1.0365 | 4.06 | 1300 | 1.1177 | |
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| 0.9853 | 4.22 | 1350 | 1.0721 | |
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| 0.9984 | 4.38 | 1400 | 0.9923 | |
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| 0.9802 | 4.53 | 1450 | 1.0079 | |
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| 1.04 | 4.69 | 1500 | 1.0198 | |
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| 1.098 | 4.84 | 1550 | 0.9788 | |
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| 1.079 | 5.0 | 1600 | 1.0291 | |
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| 1.0664 | 5.16 | 1650 | 0.9691 | |
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| 0.9715 | 5.31 | 1700 | 0.9380 | |
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| 0.9723 | 5.47 | 1750 | 1.0164 | |
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| 1.0019 | 5.62 | 1800 | 1.0064 | |
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| 0.9895 | 5.78 | 1850 | 1.0364 | |
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| 0.9835 | 5.94 | 1900 | 0.9848 | |
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| 0.994 | 6.09 | 1950 | 0.9353 | |
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| 0.9693 | 6.25 | 2000 | 0.9425 | |
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| 0.9413 | 6.41 | 2050 | 0.9173 | |
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| 0.9375 | 6.56 | 2100 | 0.9663 | |
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| 0.952 | 6.72 | 2150 | 0.8951 | |
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| 0.8927 | 6.88 | 2200 | 0.9099 | |
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| 0.8777 | 7.03 | 2250 | 0.9238 | |
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| 0.8976 | 7.19 | 2300 | 0.9715 | |
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| 0.9451 | 7.34 | 2350 | 0.9373 | |
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| 0.8972 | 7.5 | 2400 | 0.8959 | |
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| 0.9393 | 7.66 | 2450 | 1.0062 | |
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| 0.9 | 7.81 | 2500 | 0.8920 | |
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| 0.915 | 7.97 | 2550 | 0.8833 | |
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| 0.9018 | 8.12 | 2600 | 0.8671 | |
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| 0.8272 | 8.28 | 2650 | 0.9304 | |
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| 0.943 | 8.44 | 2700 | 0.8593 | |
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| 0.8667 | 8.59 | 2750 | 0.8875 | |
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| 0.871 | 8.75 | 2800 | 0.8457 | |
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| 0.9023 | 8.91 | 2850 | 0.8448 | |
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| 0.8733 | 9.06 | 2900 | 0.8261 | |
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| 0.8686 | 9.22 | 2950 | 0.8489 | |
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| 0.8412 | 9.38 | 3000 | 0.8244 | |
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| 0.8385 | 9.53 | 3050 | 0.8830 | |
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| 0.891 | 9.69 | 3100 | 0.8349 | |
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| 0.8692 | 9.84 | 3150 | 0.8672 | |
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| 0.8247 | 10.0 | 3200 | 0.8811 | |
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| 0.799 | 10.16 | 3250 | 0.8784 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
