DocumentNick / README.md
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---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- cord-layoutlmv3
model-index:
- name: DocumentNick
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# DocumentNick
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the cord-layoutlmv3 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5167
- eval_precision: 0.8758
- eval_recall: 0.8922
- eval_f1: 0.8839
- eval_accuracy: 0.8901
- eval_runtime: 10.2752
- eval_samples_per_second: 9.732
- eval_steps_per_second: 1.946
- epoch: 11.95
- step: 526
## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2500
### Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2