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--- |
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license: cc-by-nc-sa-4.0 |
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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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<!-- 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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# layoutlmv2-base-uncased_finetuned_docvqa |
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This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6030 |
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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: 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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 5.326 | 0.22 | 50 | 4.4949 | |
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| 4.292 | 0.44 | 100 | 3.9510 | |
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| 3.9419 | 0.66 | 150 | 3.9100 | |
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| 3.6895 | 0.88 | 200 | 3.5035 | |
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| 3.4052 | 1.11 | 250 | 3.4030 | |
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| 3.1405 | 1.33 | 300 | 3.2100 | |
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| 2.8966 | 1.55 | 350 | 2.9803 | |
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| 2.7874 | 1.77 | 400 | 2.7811 | |
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| 2.5385 | 1.99 | 450 | 2.4748 | |
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| 2.1532 | 2.21 | 500 | 2.5843 | |
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| 1.994 | 2.43 | 550 | 2.5459 | |
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| 1.8322 | 2.65 | 600 | 2.2316 | |
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| 1.7005 | 2.88 | 650 | 2.1888 | |
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| 1.4758 | 3.1 | 700 | 2.4578 | |
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| 1.3543 | 3.32 | 750 | 2.3368 | |
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| 1.1939 | 3.54 | 800 | 2.9737 | |
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| 1.294 | 3.76 | 850 | 2.4907 | |
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| 1.4519 | 3.98 | 900 | 1.9276 | |
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| 1.0517 | 4.2 | 950 | 2.9981 | |
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| 0.8171 | 4.42 | 1000 | 2.5618 | |
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| 1.0456 | 4.65 | 1050 | 2.3139 | |
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| 0.9222 | 4.87 | 1100 | 2.4243 | |
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| 0.758 | 5.09 | 1150 | 2.8167 | |
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| 0.7203 | 5.31 | 1200 | 2.9342 | |
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| 0.6748 | 5.53 | 1250 | 2.6396 | |
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| 0.6821 | 5.75 | 1300 | 2.5629 | |
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| 0.5898 | 5.97 | 1350 | 3.0276 | |
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| 0.3135 | 6.19 | 1400 | 3.2611 | |
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| 0.4407 | 6.42 | 1450 | 3.1793 | |
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| 0.5303 | 6.64 | 1500 | 3.0511 | |
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| 0.5294 | 6.86 | 1550 | 3.1106 | |
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| 0.3149 | 7.08 | 1600 | 3.2933 | |
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| 0.199 | 7.3 | 1650 | 3.4207 | |
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| 0.164 | 7.52 | 1700 | 3.4379 | |
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| 0.5258 | 7.74 | 1750 | 3.1339 | |
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| 0.336 | 7.96 | 1800 | 3.2394 | |
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| 0.3294 | 8.19 | 1850 | 3.0956 | |
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| 0.1587 | 8.41 | 1900 | 3.4282 | |
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| 0.2375 | 8.63 | 1950 | 3.3718 | |
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| 0.117 | 8.85 | 2000 | 3.5646 | |
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| 0.2873 | 9.07 | 2050 | 3.5213 | |
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| 0.2206 | 9.29 | 2100 | 3.5387 | |
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| 0.2503 | 9.51 | 2150 | 3.5683 | |
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| 0.0763 | 9.73 | 2200 | 3.6119 | |
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| 0.1344 | 9.96 | 2250 | 3.6030 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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