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# layoutlmv3-finetuned-cord_100

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:
- Loss: 2.5624
- Precision: 0.4115
- Recall: 0.5397
- F1: 0.4670
- Accuracy: 0.4351

## 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0.06  | 10   | 3.8065          | 0.1637    | 0.2582 | 0.2003 | 0.2585   |
| No log        | 0.12  | 20   | 3.4787          | 0.4661    | 0.3862 | 0.4224 | 0.3353   |
| No log        | 0.19  | 30   | 3.2587          | 0.4332    | 0.4731 | 0.4522 | 0.3667   |
| No log        | 0.25  | 40   | 3.0615          | 0.4144    | 0.4873 | 0.4479 | 0.3846   |
| No log        | 0.31  | 50   | 2.9052          | 0.3993    | 0.5090 | 0.4475 | 0.4024   |
| No log        | 0.38  | 60   | 2.7819          | 0.3876    | 0.5165 | 0.4429 | 0.4143   |
| No log        | 0.44  | 70   | 2.6853          | 0.3891    | 0.5202 | 0.4452 | 0.4164   |
| No log        | 0.5   | 80   | 2.6245          | 0.3942    | 0.5269 | 0.4510 | 0.4236   |
| No log        | 0.56  | 90   | 2.5777          | 0.4056    | 0.5352 | 0.4614 | 0.4312   |
| No log        | 0.62  | 100  | 2.5624          | 0.4115    | 0.5397 | 0.4670 | 0.4351   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cpu
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "datasets": ["cord-layoutlmv3"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "layoutlmv3-finetuned-cord_100", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "cord-layoutlmv3", "type": "cord-layoutlmv3", "config": "cord", "split": "test", "args": "cord"}, "metrics": [{"type": "precision", "value": 0.4115296803652968, "name": "Precision"}, {"type": "recall", "value": 0.5396706586826348, "name": "Recall"}, {"type": "f1", "value": 0.46696891191709844, "name": "F1"}, {"type": "accuracy", "value": 0.4350594227504245, "name": "Accuracy"}]}]}]}
transformers pytorch layoutlmv3 token-classification generated_from_trainer dataset:cord-layoutlmv3 license:cc-by-nc-sa-4.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #layoutlmv3 #token-classification #generated_from_trainer #dataset-cord-layoutlmv3 #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

layoutlmv3-finetuned-cord\_100
==============================


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


* Loss: 2.5624
* Precision: 0.4115
* Recall: 0.5397
* F1: 0.4670
* Accuracy: 0.4351


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: 100


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cpu
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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: 100 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cpu
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #layoutlmv3 #token-classification #generated_from_trainer #dataset-cord-layoutlmv3 #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: 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: 100 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cpu
* Datasets 2.12.0
* Tokenizers 0.13.3