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# layoutlmv3-finetuned-letter_100

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the data_cartas_layoutv3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1884
- Precision: 0.7412
- Recall: 0.8673
- F1: 0.7993
- Accuracy: 0.9632

## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 3.57  | 250  | 0.4503          | 0.2934    | 0.2242 | 0.2542 | 0.8928   |
| 0.5521        | 7.14  | 500  | 0.2833          | 0.4291    | 0.4639 | 0.4458 | 0.9209   |
| 0.5521        | 10.71 | 750  | 0.2116          | 0.5702    | 0.6753 | 0.6183 | 0.9437   |
| 0.173         | 14.29 | 1000 | 0.1786          | 0.6414    | 0.7835 | 0.7053 | 0.9562   |
| 0.173         | 17.86 | 1250 | 0.1772          | 0.6815    | 0.8492 | 0.7562 | 0.9581   |
| 0.077         | 21.43 | 1500 | 0.1737          | 0.7144    | 0.8737 | 0.7861 | 0.9616   |
| 0.077         | 25.0  | 1750 | 0.1768          | 0.7311    | 0.8724 | 0.7955 | 0.9615   |
| 0.0441        | 28.57 | 2000 | 0.1694          | 0.7726    | 0.8273 | 0.7990 | 0.9646   |
| 0.0441        | 32.14 | 2250 | 0.1874          | 0.7400    | 0.8621 | 0.7964 | 0.9620   |
| 0.0293        | 35.71 | 2500 | 0.1862          | 0.7321    | 0.8698 | 0.7951 | 0.9622   |
| 0.0293        | 39.29 | 2750 | 0.1887          | 0.7332    | 0.8711 | 0.7962 | 0.9620   |
| 0.0237        | 42.86 | 3000 | 0.1884          | 0.7412    | 0.8673 | 0.7993 | 0.9632   |


### 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"], "datasets": ["data_cartas_layoutv3"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "layoutlmv3-finetuned-letter_100", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "data_cartas_layoutv3", "type": "data_cartas_layoutv3", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "precision", "value": 0.7411894273127754, "name": "Precision"}, {"type": "recall", "value": 0.8672680412371134, "name": "Recall"}, {"type": "f1", "value": 0.7992874109263659, "name": "F1"}, {"type": "accuracy", "value": 0.9631952889969916, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard layoutlmv3 token-classification generated_from_trainer dataset:data_cartas_layoutv3 license:cc-by-nc-sa-4.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-data_cartas_layoutv3 #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

layoutlmv3-finetuned-letter\_100
================================


This model is a fine-tuned version of microsoft/layoutlmv3-base on the data\_cartas\_layoutv3 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1884
* Precision: 0.7412
* Recall: 0.8673
* F1: 0.7993
* Accuracy: 0.9632


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-06
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 3000


### Training results



### Framework versions


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



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-06
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 3000 ### 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 #layoutlmv3 #token-classification #generated_from_trainer #dataset-data_cartas_layoutv3 #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-06
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 3000 ### Training results ### Framework versions


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