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Sunilkt
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layoutlmv3-finetuned-invoice

Token Classification
Transformers
Safetensors
layoutlmv3
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: cc-by-nc-sa-4.0
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+ base_model: microsoft/layoutlmv3-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: layoutlmv3-finetuned-invoice
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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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+ # layoutlmv3-finetuned-invoice
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+
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+ This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2568
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+ - Precision: 0.7955
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+ - Recall: 0.6931
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+ - F1: 0.7407
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+ - Accuracy: 0.9524
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - training_steps: 2000
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:--------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 9.0909 | 100 | 0.8724 | 0.0270 | 0.0099 | 0.0145 | 0.7931 |
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+ | No log | 18.1818 | 200 | 0.3880 | 0.4299 | 0.4554 | 0.4423 | 0.9126 |
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+ | No log | 27.2727 | 300 | 0.2870 | 0.6 | 0.4158 | 0.4912 | 0.9229 |
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+ | No log | 36.3636 | 400 | 0.3227 | 0.6389 | 0.4554 | 0.5318 | 0.9242 |
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+ | 0.6024 | 45.4545 | 500 | 0.3251 | 0.6092 | 0.5248 | 0.5638 | 0.9280 |
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+ | 0.6024 | 54.5455 | 600 | 0.2188 | 0.6842 | 0.6436 | 0.6633 | 0.9422 |
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+ | 0.6024 | 63.6364 | 700 | 0.2146 | 0.7159 | 0.6238 | 0.6667 | 0.9447 |
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+ | 0.6024 | 72.7273 | 800 | 0.2138 | 0.8202 | 0.7228 | 0.7684 | 0.9563 |
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+ | 0.6024 | 81.8182 | 900 | 0.2128 | 0.7927 | 0.6436 | 0.7104 | 0.9499 |
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+ | 0.0428 | 90.9091 | 1000 | 0.2400 | 0.7753 | 0.6832 | 0.7263 | 0.9512 |
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+ | 0.0428 | 100.0 | 1100 | 0.2498 | 0.7821 | 0.6040 | 0.6816 | 0.9434 |
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+ | 0.0428 | 109.0909 | 1200 | 0.2614 | 0.7805 | 0.6337 | 0.6995 | 0.9447 |
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+ | 0.0428 | 118.1818 | 1300 | 0.2742 | 0.7821 | 0.6040 | 0.6816 | 0.9447 |
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+ | 0.0428 | 127.2727 | 1400 | 0.2744 | 0.7471 | 0.6436 | 0.6915 | 0.9473 |
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+ | 0.0091 | 136.3636 | 1500 | 0.2568 | 0.7955 | 0.6931 | 0.7407 | 0.9524 |
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+ | 0.0091 | 145.4545 | 1600 | 0.2711 | 0.7701 | 0.6634 | 0.7128 | 0.9486 |
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+ | 0.0091 | 154.5455 | 1700 | 0.3043 | 0.7778 | 0.6238 | 0.6923 | 0.9434 |
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+ | 0.0091 | 163.6364 | 1800 | 0.2746 | 0.7683 | 0.6238 | 0.6885 | 0.9434 |
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+ | 0.0091 | 172.7273 | 1900 | 0.2646 | 0.7955 | 0.6931 | 0.7407 | 0.9524 |
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+ | 0.0056 | 181.8182 | 2000 | 0.2681 | 0.7955 | 0.6931 | 0.7407 | 0.9524 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.0.dev0
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+ - Pytorch 2.2.2+cpu
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1