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detr_finetuned

Object Detection
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Safetensors
table-transformer
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End of training

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  1. README.md +97 -0
  2. config.json +61 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +26 -0
  5. runs/Mar12_07-57-27_7def8fc1ca8d/events.out.tfevents.1741766377.7def8fc1ca8d.1062.0 +3 -0
  6. runs/Mar12_08-02-24_7def8fc1ca8d/events.out.tfevents.1741766556.7def8fc1ca8d.5547.0 +3 -0
  7. runs/Mar12_08-02-24_7def8fc1ca8d/events.out.tfevents.1741766998.7def8fc1ca8d.5547.1 +3 -0
  8. runs/Mar12_08-02-24_7def8fc1ca8d/events.out.tfevents.1741767632.7def8fc1ca8d.5547.2 +3 -0
  9. runs/Mar12_08-02-24_7def8fc1ca8d/events.out.tfevents.1741769243.7def8fc1ca8d.5547.3 +3 -0
  10. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ base_model: apkonsta/table-transformer-detection-ifrs
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: detr_finetuned
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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_finetuned
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+
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+ This model is a fine-tuned version of [apkonsta/table-transformer-detection-ifrs](https://huggingface.co/apkonsta/table-transformer-detection-ifrs) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 4914.5493
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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: 1e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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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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+ - num_epochs: 10
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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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+ | 4887.0844 | 0.2381 | 100 | 4915.8008 |
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+ | 4806.7622 | 0.4762 | 200 | 4915.0762 |
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+ | 4883.3641 | 0.7143 | 300 | 4914.7651 |
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+ | 4869.7525 | 0.9524 | 400 | 4914.6387 |
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+ | 4809.9978 | 1.1905 | 500 | 4914.6133 |
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+ | 4820.81 | 1.4286 | 600 | 4914.6948 |
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+ | 4779.5872 | 1.6667 | 700 | 4914.6743 |
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+ | 5094.1991 | 1.9048 | 800 | 4914.5752 |
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+ | 4851.7441 | 2.1429 | 900 | 4914.6494 |
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+ | 4928.8484 | 2.3810 | 1000 | 4914.5767 |
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+ | 4852.6178 | 2.6190 | 1100 | 4914.5840 |
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+ | 4855.8131 | 2.8571 | 1200 | 4914.5991 |
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+ | 4948.5747 | 3.0952 | 1300 | 4914.5967 |
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+ | 4887.945 | 3.3333 | 1400 | 4914.5645 |
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+ | 4900.1669 | 3.5714 | 1500 | 4914.5747 |
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+ | 4937.1328 | 3.8095 | 1600 | 4914.5571 |
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+ | 4792.3219 | 4.0476 | 1700 | 4914.6787 |
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+ | 4842.8072 | 4.2857 | 1800 | 4914.5640 |
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+ | 4914.0503 | 4.5238 | 1900 | 4914.6113 |
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+ | 4892.0153 | 4.7619 | 2000 | 4914.5693 |
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+ | 4882.0288 | 5.0 | 2100 | 4914.5630 |
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+ | 4903.9891 | 5.2381 | 2200 | 4914.5679 |
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+ | 4870.5566 | 5.4762 | 2300 | 4914.5688 |
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+ | 4919.3287 | 5.7143 | 2400 | 4914.5508 |
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+ | 4927.9272 | 5.9524 | 2500 | 4914.5488 |
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+ | 4981.8925 | 6.1905 | 2600 | 4914.5537 |
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+ | 4864.6322 | 6.4286 | 2700 | 4914.5835 |
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+ | 4794.4006 | 6.6667 | 2800 | 4914.5820 |
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+ | 4878.885 | 6.9048 | 2900 | 4914.5488 |
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+ | 4967.0887 | 7.1429 | 3000 | 4914.5518 |
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+ | 4937.0766 | 7.3810 | 3100 | 4914.5464 |
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+ | 4829.3891 | 7.6190 | 3200 | 4914.5493 |
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+ | 4812.0778 | 7.8571 | 3300 | 4914.5459 |
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+ | 4823.5034 | 8.0952 | 3400 | 4914.5444 |
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+ | 4919.2544 | 8.3333 | 3500 | 4914.5474 |
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+ | 4838.375 | 8.5714 | 3600 | 4914.5581 |
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+ | 4832.6153 | 8.8095 | 3700 | 4914.5513 |
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+ | 4787.5813 | 9.0476 | 3800 | 4914.5464 |
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+ | 4862.2234 | 9.2857 | 3900 | 4914.5464 |
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+ | 4878.2669 | 9.5238 | 4000 | 4914.5474 |
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+ | 4933.3856 | 9.7619 | 4100 | 4914.5488 |
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+ | 4945.8159 | 10.0 | 4200 | 4914.5493 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.3
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+ - Pytorch 2.5.1+cu124
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+ - Tokenizers 0.21.0
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+ "use_pretrained_backbone": true,
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