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# arquivo-layoutxml-model

This model is a fine-tuned version of [microsoft/layoutxlm-base](https://huggingface.co/microsoft/layoutxlm-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2997
- Ategory Precision: 0.8719
- Ategory Recall: 0.8491
- Ategory F1: 0.8603
- Ategory Number: 497
- Itle Precision: 0.8745
- Itle Recall: 0.8971
- Itle F1: 0.8857
- Itle Number: 2508
- One Precision: 0.8855
- One Recall: 0.8855
- One F1: 0.8855
- One Number: 2951
- Ubtitle Precision: 0.9494
- Ubtitle Recall: 0.9774
- Ubtitle F1: 0.9632
- Ubtitle Number: 23695
- Overall Precision: 0.9356
- Overall Recall: 0.9593
- Overall F1: 0.9473
- Overall Accuracy: 0.9629

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "arquivo-layoutxml-model", "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 




# arquivo-layoutxml-model

This model is a fine-tuned version of microsoft/layoutxlm-base on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2997
- Ategory Precision: 0.8719
- Ategory Recall: 0.8491
- Ategory F1: 0.8603
- Ategory Number: 497
- Itle Precision: 0.8745
- Itle Recall: 0.8971
- Itle F1: 0.8857
- Itle Number: 2508
- One Precision: 0.8855
- One Recall: 0.8855
- One F1: 0.8855
- One Number: 2951
- Ubtitle Precision: 0.9494
- Ubtitle Recall: 0.9774
- Ubtitle F1: 0.9632
- Ubtitle Number: 23695
- Overall Precision: 0.9356
- Overall Recall: 0.9593
- Overall F1: 0.9473
- Overall Accuracy: 0.9629

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

# arquivo-layoutxml-model

This model is a fine-tuned version of microsoft/layoutxlm-base on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2997
- Ategory Precision: 0.8719
- Ategory Recall: 0.8491
- Ategory F1: 0.8603
- Ategory Number: 497
- Itle Precision: 0.8745
- Itle Recall: 0.8971
- Itle F1: 0.8857
- Itle Number: 2508
- One Precision: 0.8855
- One Recall: 0.8855
- One F1: 0.8855
- One Number: 2951
- Ubtitle Precision: 0.9494
- Ubtitle Recall: 0.9774
- Ubtitle F1: 0.9632
- Ubtitle Number: 23695
- Overall Precision: 0.9356
- Overall Recall: 0.9593
- Overall F1: 0.9473
- Overall Accuracy: 0.9629 ## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+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 
 # arquivo-layoutxml-model

This model is a fine-tuned version of microsoft/layoutxlm-base on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2997
- Ategory Precision: 0.8719
- Ategory Recall: 0.8491
- Ategory F1: 0.8603
- Ategory Number: 497
- Itle Precision: 0.8745
- Itle Recall: 0.8971
- Itle F1: 0.8857
- Itle Number: 2508
- One Precision: 0.8855
- One Recall: 0.8855
- One F1: 0.8855
- One Number: 2951
- Ubtitle Precision: 0.9494
- Ubtitle Recall: 0.9774
- Ubtitle F1: 0.9632
- Ubtitle Number: 23695
- Overall Precision: 0.9356
- Overall Recall: 0.9593
- Overall F1: 0.9473
- Overall Accuracy: 0.9629 ## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+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 
# arquivo-layoutxml-model

This model is a fine-tuned version of microsoft/layoutxlm-base on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2997
- Ategory Precision: 0.8719
- Ategory Recall: 0.8491
- Ategory F1: 0.8603
- Ategory Number: 497
- Itle Precision: 0.8745
- Itle Recall: 0.8971
- Itle F1: 0.8857
- Itle Number: 2508
- One Precision: 0.8855
- One Recall: 0.8855
- One F1: 0.8855
- One Number: 2951
- Ubtitle Precision: 0.9494
- Ubtitle Recall: 0.9774
- Ubtitle F1: 0.9632
- Ubtitle Number: 23695
- Overall Precision: 0.9356
- Overall Recall: 0.9593
- Overall F1: 0.9473
- Overall Accuracy: 0.9629## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP### Training results### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3