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# Is_there_relation

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1011
- Macro F1: 0.9873
- Precision: 0.9875
- Recall: 0.9873
- Kappa: 0.9708
- Accuracy: 0.9873

## 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: 16
- eval_batch_size: 128
- seed: 25
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Precision | Recall | Kappa  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 280  | 0.0828          | 0.9746   | 0.9747    | 0.9745 | 0.9413 | 0.9745   |
| 0.1162        | 2.0   | 560  | 0.1149          | 0.9684   | 0.9699    | 0.9682 | 0.9278 | 0.9682   |
| 0.1162        | 3.0   | 840  | 0.0942          | 0.9852   | 0.9855    | 0.9851 | 0.9659 | 0.9851   |
| 0.0231        | 4.0   | 1120 | 0.0749          | 0.9873   | 0.9875    | 0.9873 | 0.9708 | 0.9873   |
| 0.0231        | 5.0   | 1400 | 0.1058          | 0.9873   | 0.9875    | 0.9873 | 0.9708 | 0.9873   |
| 0.0084        | 6.0   | 1680 | 0.1145          | 0.9873   | 0.9875    | 0.9873 | 0.9708 | 0.9873   |
| 0.0084        | 7.0   | 1960 | 0.0813          | 0.9852   | 0.9853    | 0.9851 | 0.9658 | 0.9851   |
| 0.0056        | 8.0   | 2240 | 0.1235          | 0.9873   | 0.9875    | 0.9873 | 0.9708 | 0.9873   |
| 0.0022        | 9.0   | 2520 | 0.0928          | 0.9894   | 0.9895    | 0.9894 | 0.9756 | 0.9894   |
| 0.0022        | 10.0  | 2800 | 0.1079          | 0.9873   | 0.9875    | 0.9873 | 0.9708 | 0.9873   |
| 0.0019        | 11.0  | 3080 | 0.0796          | 0.9894   | 0.9895    | 0.9894 | 0.9756 | 0.9894   |
| 0.0019        | 12.0  | 3360 | 0.1084          | 0.9873   | 0.9875    | 0.9873 | 0.9708 | 0.9873   |
| 0.0004        | 13.0  | 3640 | 0.1099          | 0.9873   | 0.9875    | 0.9873 | 0.9708 | 0.9873   |
| 0.0004        | 14.0  | 3920 | 0.1233          | 0.9873   | 0.9875    | 0.9873 | 0.9708 | 0.9873   |
| 0.0005        | 15.0  | 4200 | 0.1011          | 0.9873   | 0.9875    | 0.9873 | 0.9708 | 0.9873   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "accuracy"], "model-index": [{"name": "Is_there_relation", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

Is\_there\_relation
===================


This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1011
* Macro F1: 0.9873
* Precision: 0.9875
* Recall: 0.9873
* Kappa: 0.9708
* Accuracy: 0.9873


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: 16
* eval\_batch\_size: 128
* seed: 25
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 128
* seed: 25
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 128
* seed: 25
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Tokenizers 0.13.3