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# layoutlmv3-finetuned-cord_800

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: 0.2042
- Precision: 0.9445
- Recall: 0.9558
- F1: 0.9501
- Accuracy: 0.9605

## 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: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.56  | 250  | 0.9737          | 0.7787    | 0.8166 | 0.7972 | 0.8188   |
| 1.3706        | 3.12  | 500  | 0.5489          | 0.8480    | 0.8645 | 0.8562 | 0.8680   |
| 1.3706        | 4.69  | 750  | 0.3857          | 0.8913    | 0.9087 | 0.8999 | 0.9147   |
| 0.3693        | 6.25  | 1000 | 0.3192          | 0.9117    | 0.9274 | 0.9195 | 0.9317   |
| 0.3693        | 7.81  | 1250 | 0.2816          | 0.9189    | 0.9326 | 0.9257 | 0.9355   |
| 0.1903        | 9.38  | 1500 | 0.2521          | 0.9277    | 0.9409 | 0.9342 | 0.9465   |
| 0.1903        | 10.94 | 1750 | 0.2353          | 0.9357    | 0.9476 | 0.9416 | 0.9550   |
| 0.1231        | 12.5  | 2000 | 0.2361          | 0.9293    | 0.9446 | 0.9369 | 0.9516   |
| 0.1231        | 14.06 | 2250 | 0.2194          | 0.9402    | 0.9528 | 0.9465 | 0.9576   |
| 0.0766        | 15.62 | 2500 | 0.2133          | 0.9416    | 0.9528 | 0.9472 | 0.9580   |
| 0.0766        | 17.19 | 2750 | 0.2117          | 0.9438    | 0.9558 | 0.9498 | 0.9597   |
| 0.0585        | 18.75 | 3000 | 0.2152          | 0.9417    | 0.9551 | 0.9483 | 0.9605   |
| 0.0585        | 20.31 | 3250 | 0.2070          | 0.9431    | 0.9551 | 0.9491 | 0.9588   |
| 0.0454        | 21.88 | 3500 | 0.2093          | 0.9489    | 0.9588 | 0.9538 | 0.9622   |
| 0.0454        | 23.44 | 3750 | 0.2034          | 0.9453    | 0.9566 | 0.9509 | 0.9610   |
| 0.0409        | 25.0  | 4000 | 0.2042          | 0.9445    | 0.9558 | 0.9501 | 0.9605   |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"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_800", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "cord-layoutlmv3", "type": "cord-layoutlmv3", "config": "cord", "split": "train", "args": "cord"}, "metrics": [{"type": "precision", "value": 0.9445266272189349, "name": "Precision"}, {"type": "recall", "value": 0.9558383233532934, "name": "Recall"}, {"type": "f1", "value": 0.9501488095238095, "name": "F1"}, {"type": "accuracy", "value": 0.9605263157894737, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard 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 #tensorboard #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\_800
==============================


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: 0.2042
* Precision: 0.9445
* Recall: 0.9558
* F1: 0.9501
* Accuracy: 0.9605


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: 4000


### Training results



### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### 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: 4000 ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #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: 4000 ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #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: 4000### Training results### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1