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layoutlmv2-base-uncased_finetuned_docvqa

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layoutlmv2-base-uncased_finetuned_docvqa

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Files changed (10) hide show
  1. README.md +146 -0
  2. config.json +132 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +14 -0
  5. runs/Nov10_15-33-36_da2e60d1ff88/events.out.tfevents.1699630421.da2e60d1ff88.32254.0 +3 -0
  6. special_tokens_map.json +37 -0
  7. tokenizer.json +0 -0
  8. tokenizer_config.json +79 -0
  9. training_args.bin +3 -0
  10. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ license: cc-by-nc-sa-4.0
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+ base_model: microsoft/layoutlmv2-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: layoutlmv2-base-uncased_finetuned_docvqa
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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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+ # layoutlmv2-base-uncased_finetuned_docvqa
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+
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+ This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 4.9097
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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: 4
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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: 20
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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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+ | 5.3187 | 0.22 | 50 | 4.6843 |
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+ | 4.5031 | 0.44 | 100 | 4.1274 |
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+ | 4.128 | 0.66 | 150 | 3.7921 |
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+ | 3.9091 | 0.88 | 200 | 3.6115 |
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+ | 3.6889 | 1.11 | 250 | 3.5696 |
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+ | 3.1707 | 1.33 | 300 | 3.1811 |
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+ | 3.0354 | 1.55 | 350 | 2.8562 |
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+ | 2.7856 | 1.77 | 400 | 2.7444 |
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+ | 2.4529 | 1.99 | 450 | 2.7386 |
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+ | 1.9655 | 2.21 | 500 | 2.6058 |
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+ | 1.9712 | 2.43 | 550 | 2.3241 |
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+ | 1.9305 | 2.65 | 600 | 2.2414 |
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+ | 1.7701 | 2.88 | 650 | 2.1765 |
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+ | 1.3844 | 3.1 | 700 | 2.7470 |
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+ | 1.4493 | 3.32 | 750 | 2.3821 |
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+ | 1.2487 | 3.54 | 800 | 2.0868 |
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+ | 1.3189 | 3.76 | 850 | 2.5860 |
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+ | 1.3709 | 3.98 | 900 | 2.4280 |
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+ | 1.1087 | 4.2 | 950 | 2.5985 |
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+ | 0.9481 | 4.42 | 1000 | 3.3342 |
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+ | 1.0106 | 4.65 | 1050 | 3.0318 |
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+ | 0.9703 | 4.87 | 1100 | 2.7671 |
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+ | 0.788 | 5.09 | 1150 | 3.0565 |
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+ | 0.6952 | 5.31 | 1200 | 3.3631 |
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+ | 0.8017 | 5.53 | 1250 | 3.2544 |
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+ | 0.6489 | 5.75 | 1300 | 3.0772 |
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+ | 0.7419 | 5.97 | 1350 | 2.6226 |
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+ | 0.558 | 6.19 | 1400 | 3.5186 |
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+ | 0.5727 | 6.42 | 1450 | 3.3600 |
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+ | 0.5322 | 6.64 | 1500 | 3.5181 |
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+ | 0.6472 | 6.86 | 1550 | 3.6967 |
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+ | 0.5805 | 7.08 | 1600 | 3.2425 |
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+ | 0.4877 | 7.3 | 1650 | 3.4871 |
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+ | 0.273 | 7.52 | 1700 | 3.5272 |
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+ | 0.5527 | 7.74 | 1750 | 3.0758 |
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+ | 0.2936 | 7.96 | 1800 | 3.3492 |
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+ | 0.2585 | 8.19 | 1850 | 3.4836 |
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+ | 0.5038 | 8.41 | 1900 | 3.3159 |
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+ | 0.3943 | 8.63 | 1950 | 3.3977 |
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+ | 0.3129 | 8.85 | 2000 | 3.8042 |
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+ | 0.2977 | 9.07 | 2050 | 3.7062 |
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+ | 0.2695 | 9.29 | 2100 | 3.7420 |
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+ | 0.363 | 9.51 | 2150 | 3.6655 |
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+ | 0.1834 | 9.73 | 2200 | 3.7858 |
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+ | 0.3347 | 9.96 | 2250 | 3.9257 |
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+ | 0.2159 | 10.18 | 2300 | 3.9075 |
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+ | 0.2691 | 10.4 | 2350 | 3.8001 |
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+ | 0.2965 | 10.62 | 2400 | 3.6177 |
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+ | 0.3078 | 10.84 | 2450 | 3.8440 |
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+ | 0.1397 | 11.06 | 2500 | 4.0490 |
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+ | 0.052 | 11.28 | 2550 | 4.2137 |
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+ | 0.1741 | 11.5 | 2600 | 4.2273 |
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+ | 0.2956 | 11.73 | 2650 | 3.8075 |
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+ | 0.2098 | 11.95 | 2700 | 4.1653 |
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+ | 0.1466 | 12.17 | 2750 | 4.2080 |
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+ | 0.1378 | 12.39 | 2800 | 4.0473 |
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+ | 0.1864 | 12.61 | 2850 | 4.0665 |
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+ | 0.1938 | 12.83 | 2900 | 4.1019 |
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+ | 0.2332 | 13.05 | 2950 | 3.9249 |
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+ | 0.0486 | 13.27 | 3000 | 4.2374 |
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+ | 0.223 | 13.5 | 3050 | 4.1405 |
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+ | 0.1387 | 13.72 | 3100 | 4.1833 |
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+ | 0.1447 | 13.94 | 3150 | 4.0949 |
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+ | 0.0265 | 14.16 | 3200 | 4.2652 |
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+ | 0.0253 | 14.38 | 3250 | 4.5294 |
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+ | 0.1781 | 14.6 | 3300 | 4.5310 |
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+ | 0.0676 | 14.82 | 3350 | 4.3897 |
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+ | 0.0692 | 15.04 | 3400 | 4.3176 |
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+ | 0.1093 | 15.27 | 3450 | 4.3505 |
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+ | 0.0219 | 15.49 | 3500 | 4.4436 |
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+ | 0.0834 | 15.71 | 3550 | 4.4736 |
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+ | 0.0728 | 15.93 | 3600 | 4.5234 |
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+ | 0.0612 | 16.15 | 3650 | 4.6432 |
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+ | 0.0844 | 16.37 | 3700 | 4.5729 |
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+ | 0.0269 | 16.59 | 3750 | 4.7230 |
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+ | 0.037 | 16.81 | 3800 | 4.7512 |
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+ | 0.0532 | 17.04 | 3850 | 4.8247 |
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+ | 0.0042 | 17.26 | 3900 | 4.8263 |
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+ | 0.0684 | 17.48 | 3950 | 4.7495 |
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+ | 0.0058 | 17.7 | 4000 | 4.7748 |
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+ | 0.0158 | 17.92 | 4050 | 4.8827 |
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+ | 0.0059 | 18.14 | 4100 | 4.8746 |
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+ | 0.0217 | 18.36 | 4150 | 4.8981 |
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+ | 0.0725 | 18.58 | 4200 | 4.9908 |
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+ | 0.0399 | 18.81 | 4250 | 4.8712 |
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+ | 0.0478 | 19.03 | 4300 | 4.9006 |
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+ | 0.0212 | 19.25 | 4350 | 4.9160 |
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+ | 0.0269 | 19.47 | 4400 | 4.9076 |
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+ | 0.0317 | 19.69 | 4450 | 4.9081 |
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+ | 0.0233 | 19.91 | 4500 | 4.9097 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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+ "fast_qkv": true,
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+ "has_visual_segment_embedding": true,
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