
<!-- 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. -->

# EElayoutlmv3_jordyvl_rvl_cdip_easyocr_2023-05-22_loss_subgraphs

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2391
- Accuracy: 0.9343
- Exit 0 Accuracy: 0.3283
- Exit 1 Accuracy: 0.4678
- Exit 2 Accuracy: 0.8356
- Exit 3 Accuracy: 0.9082
- Exit 4 Accuracy: 0.9331

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Exit 0 Accuracy | Exit 1 Accuracy | Exit 2 Accuracy | Exit 3 Accuracy | Exit 4 Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:---------------:|:---------------:|:---------------:|:---------------:|
| 0.4036        | 1.0   | 1250 | 0.3090          | 0.9140   | 0.2036          | 0.3108          | 0.7504          | 0.8722          | 0.9108          |
| 0.2783        | 2.0   | 2500 | 0.2730          | 0.9221   | 0.2715          | 0.3928          | 0.7959          | 0.8902          | 0.9227          |
| 0.2376        | 3.0   | 3750 | 0.2487          | 0.9284   | 0.2865          | 0.4313          | 0.8182          | 0.9000          | 0.9280          |
| 0.1984        | 4.0   | 5000 | 0.2446          | 0.9314   | 0.3150          | 0.4529          | 0.8282          | 0.9033          | 0.9301          |
| 0.1729        | 5.0   | 6250 | 0.2424          | 0.9327   | 0.3240          | 0.4636          | 0.8331          | 0.9076          | 0.9323          |
| 0.1524        | 6.0   | 7500 | 0.2391          | 0.9343   | 0.3283          | 0.4678          | 0.8356          | 0.9082          | 0.9331          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "EElayoutlmv3_jordyvl_rvl_cdip_easyocr_2023-05-22_loss_subgraphs", "results": []}]}
transformers pytorch layoutlmv3 text-classification generated_from_trainer license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #layoutlmv3 #text-classification #generated_from_trainer #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 

EElayoutlmv3\_jordyvl\_rvl\_cdip\_easyocr\_2023-05-22\_loss\_subgraphs
======================================================================


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


* Loss: 0.2391
* Accuracy: 0.9343
* Exit 0 Accuracy: 0.3283
* Exit 1 Accuracy: 0.4678
* Exit 2 Accuracy: 0.8356
* Exit 3 Accuracy: 0.9082
* Exit 4 Accuracy: 0.9331


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: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 4
* seed: 42
* gradient\_accumulation\_steps: 32
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1.post200
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 4
* seed: 42
* gradient\_accumulation\_steps: 32
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1.post200
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #layoutlmv3 #text-classification #generated_from_trainer #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 4
* seed: 42
* gradient\_accumulation\_steps: 32
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1.post200
* Datasets 2.9.0
* Tokenizers 0.13.2