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# layoutxlm-tokenclass-finetuned

This model is a fine-tuned version of [microsoft/layoutxlm-base](https://huggingface.co/microsoft/layoutxlm-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2039
- Answer Precision: 0.9231
- Answer Recall: 0.9180
- Answer F1: 0.9205
- Answer Number: 366
- Header Precision: 0.8194
- Header Recall: 0.9219
- Header F1: 0.8676
- Header Number: 64
- Question Precision: 0.9115
- Question Recall: 0.9428
- Question F1: 0.9269
- Question Number: 437
- Overall Precision: 0.9088
- Overall Recall: 0.9308
- Overall F1: 0.9197
- Overall Accuracy: 0.9758

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 5000

### Training results



### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "layoutxlm-tokenclass-finetuned", "results": []}]}
transformers pytorch tensorboard layoutlmv2 token-classification generated_from_trainer license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #layoutlmv2 #token-classification #generated_from_trainer #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 




# layoutxlm-tokenclass-finetuned

This model is a fine-tuned version of microsoft/layoutxlm-base on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2039
- Answer Precision: 0.9231
- Answer Recall: 0.9180
- Answer F1: 0.9205
- Answer Number: 366
- Header Precision: 0.8194
- Header Recall: 0.9219
- Header F1: 0.8676
- Header Number: 64
- Question Precision: 0.9115
- Question Recall: 0.9428
- Question F1: 0.9269
- Question Number: 437
- Overall Precision: 0.9088
- Overall Recall: 0.9308
- Overall F1: 0.9197
- Overall Accuracy: 0.9758

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 5000

### Training results



### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

# layoutxlm-tokenclass-finetuned

This model is a fine-tuned version of microsoft/layoutxlm-base on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2039
- Answer Precision: 0.9231
- Answer Recall: 0.9180
- Answer F1: 0.9205
- Answer Number: 366
- Header Precision: 0.8194
- Header Recall: 0.9219
- Header F1: 0.8676
- Header Number: 64
- Question Precision: 0.9115
- Question Recall: 0.9428
- Question F1: 0.9269
- Question Number: 437
- Overall Precision: 0.9088
- Overall Recall: 0.9308
- Overall F1: 0.9197
- Overall Accuracy: 0.9758 ## Model description

More information needed ## Intended uses & limitations

More information needed ## Training and evaluation data

More information needed ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 5000 ### Training results ### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #layoutlmv2 #token-classification #generated_from_trainer #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 # layoutxlm-tokenclass-finetuned

This model is a fine-tuned version of microsoft/layoutxlm-base on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2039
- Answer Precision: 0.9231
- Answer Recall: 0.9180
- Answer F1: 0.9205
- Answer Number: 366
- Header Precision: 0.8194
- Header Recall: 0.9219
- Header F1: 0.8676
- Header Number: 64
- Question Precision: 0.9115
- Question Recall: 0.9428
- Question F1: 0.9269
- Question Number: 437
- Overall Precision: 0.9088
- Overall Recall: 0.9308
- Overall F1: 0.9197
- Overall Accuracy: 0.9758 ## Model description

More information needed ## Intended uses & limitations

More information needed ## Training and evaluation data

More information needed ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 5000 ### Training results ### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3