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# finetuned-ner-hadith-fistsubisa1

This model is a fine-tuned version of [hatmimoha/arabic-ner](https://huggingface.co/hatmimoha/arabic-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4707
- Precision: 0.3641
- Recall: 0.7
- F1: 0.4790
- Accuracy: 0.8111

## 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: 2
- eval_batch_size: 3
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 312  | 0.4445          | 0.3683    | 0.6555 | 0.4716 | 0.8105   |
| 0.5169        | 2.0   | 624  | 0.4690          | 0.3528    | 0.6956 | 0.4682 | 0.8076   |
| 0.5169        | 3.0   | 936  | 0.4314          | 0.3405    | 0.6781 | 0.4534 | 0.8099   |
| 0.3852        | 4.0   | 1248 | 0.4360          | 0.3509    | 0.6774 | 0.4623 | 0.8132   |
| 0.3269        | 5.0   | 1560 | 0.4707          | 0.3641    | 0.7    | 0.4790 | 0.8111   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "finetuned-ner-hadith-fistsubisa1", "results": []}]}
transformers pytorch bert token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

finetuned-ner-hadith-fistsubisa1
================================


This model is a fine-tuned version of hatmimoha/arabic-ner on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4707
* Precision: 0.3641
* Recall: 0.7
* F1: 0.4790
* Accuracy: 0.8111


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: 2
* eval\_batch\_size: 3
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 2
* eval\_batch\_size: 3
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #bert #token-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: 2
* eval\_batch\_size: 3
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #bert #token-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: 2
* eval\_batch\_size: 3
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1