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layoutlmv3-funsd

Token Classification
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layoutlmv3
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  1. README.md +17 -17
  2. logs/events.out.tfevents.1704302706.5d6f2496a87d.26.0 +2 -2
  3. logs/events.out.tfevents.1704305121.5d6f2496a87d.26.1 +3 -0
  4. model.safetensors +1 -1
  5. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.8190
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- - Precision: 0.8973
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- - Recall: 0.9111
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- - F1: 0.9041
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- - Accuracy: 0.8473
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  ## Model description
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@@ -44,8 +44,8 @@ More information needed
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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: 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
@@ -56,16 +56,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 5.26 | 100 | 0.5958 | 0.8295 | 0.8723 | 0.8504 | 0.8178 |
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- | No log | 10.53 | 200 | 0.6181 | 0.8505 | 0.8932 | 0.8713 | 0.8241 |
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- | No log | 15.79 | 300 | 0.6992 | 0.8841 | 0.9021 | 0.8930 | 0.8470 |
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- | No log | 21.05 | 400 | 0.8182 | 0.8931 | 0.9006 | 0.8969 | 0.8328 |
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- | 0.3071 | 26.32 | 500 | 0.8190 | 0.8973 | 0.9111 | 0.9041 | 0.8473 |
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- | 0.3071 | 31.58 | 600 | 0.9001 | 0.8812 | 0.9061 | 0.8935 | 0.8326 |
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- | 0.3071 | 36.84 | 700 | 0.9112 | 0.8958 | 0.9101 | 0.9029 | 0.8435 |
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- | 0.3071 | 42.11 | 800 | 0.9196 | 0.8951 | 0.9026 | 0.8988 | 0.8408 |
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- | 0.3071 | 47.37 | 900 | 0.9256 | 0.8990 | 0.9061 | 0.9025 | 0.8454 |
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- | 0.0245 | 52.63 | 1000 | 0.9584 | 0.8962 | 0.9046 | 0.9004 | 0.8431 |
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  ### Framework versions
 
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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: 0.8428
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+ - Precision: 0.8993
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+ - Recall: 0.9046
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+ - F1: 0.9019
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+ - Accuracy: 0.8354
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  ## Model description
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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: 4
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+ - eval_batch_size: 4
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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 Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 2.63 | 100 | 0.6294 | 0.7864 | 0.8286 | 0.8070 | 0.7966 |
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+ | No log | 5.26 | 200 | 0.5034 | 0.8389 | 0.8793 | 0.8586 | 0.8343 |
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+ | No log | 7.89 | 300 | 0.5673 | 0.8597 | 0.9011 | 0.8799 | 0.8416 |
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+ | No log | 10.53 | 400 | 0.5730 | 0.8783 | 0.9106 | 0.8941 | 0.8395 |
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+ | 0.4463 | 13.16 | 500 | 0.6630 | 0.8923 | 0.9016 | 0.8970 | 0.8412 |
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+ | 0.4463 | 15.79 | 600 | 0.7048 | 0.8850 | 0.8947 | 0.8898 | 0.8329 |
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+ | 0.4463 | 18.42 | 700 | 0.7772 | 0.8925 | 0.9071 | 0.8997 | 0.8317 |
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+ | 0.4463 | 21.05 | 800 | 0.8408 | 0.8959 | 0.9016 | 0.8987 | 0.8313 |
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+ | 0.4463 | 23.68 | 900 | 0.8580 | 0.8918 | 0.9051 | 0.8984 | 0.8313 |
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+ | 0.0611 | 26.32 | 1000 | 0.8428 | 0.8993 | 0.9046 | 0.9019 | 0.8354 |
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  ### Framework versions
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