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# layoutlmv3-finetuned-generated

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the generated dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0009
- eval_precision: 1.0
- eval_recall: 1.0
- eval_f1: 1.0
- eval_accuracy: 1.0
- eval_runtime: 4.3549
- eval_samples_per_second: 11.481
- eval_steps_per_second: 5.741
- epoch: 30.0
- step: 1500

## 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
- training_steps: 2500

### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "datasets": ["generated"], "model-index": [{"name": "layoutlmv3-finetuned-generated", "results": []}]}
transformers pytorch tensorboard layoutlmv3 token-classification generated_from_trainer dataset:generated license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-generated #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 




# layoutlmv3-finetuned-generated

This model is a fine-tuned version of microsoft/layoutlmv3-base on the generated dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0009
- eval_precision: 1.0
- eval_recall: 1.0
- eval_f1: 1.0
- eval_accuracy: 1.0
- eval_runtime: 4.3549
- eval_samples_per_second: 11.481
- eval_steps_per_second: 5.741
- epoch: 30.0
- step: 1500

## 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
- training_steps: 2500

### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

# layoutlmv3-finetuned-generated

This model is a fine-tuned version of microsoft/layoutlmv3-base on the generated dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0009
- eval_precision: 1.0
- eval_recall: 1.0
- eval_f1: 1.0
- eval_accuracy: 1.0
- eval_runtime: 4.3549
- eval_samples_per_second: 11.481
- eval_steps_per_second: 5.741
- epoch: 30.0
- step: 1500 ## 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
- training_steps: 2500 ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-generated #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 # layoutlmv3-finetuned-generated

This model is a fine-tuned version of microsoft/layoutlmv3-base on the generated dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0009
- eval_precision: 1.0
- eval_recall: 1.0
- eval_f1: 1.0
- eval_accuracy: 1.0
- eval_runtime: 4.3549
- eval_samples_per_second: 11.481
- eval_steps_per_second: 5.741
- epoch: 30.0
- step: 1500 ## 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
- training_steps: 2500 ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-generated #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
# layoutlmv3-finetuned-generated

This model is a fine-tuned version of microsoft/layoutlmv3-base on the generated dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0009
- eval_precision: 1.0
- eval_recall: 1.0
- eval_f1: 1.0
- eval_accuracy: 1.0
- eval_runtime: 4.3549
- eval_samples_per_second: 11.481
- eval_steps_per_second: 5.741
- epoch: 30.0
- step: 1500## 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
- training_steps: 2500### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3