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# model_from_berturk_Feb_5_TrainTestSplit

This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3125
- Precision: 0.9120
- Recall: 0.9126
- F1: 0.9123
- Accuracy: 0.9376

## 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: 32
- eval_batch_size: 32
- seed: 42
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 185  | 0.2333          | 0.9065    | 0.9066 | 0.9066 | 0.9343   |
| No log        | 2.0   | 370  | 0.2115          | 0.9122    | 0.9143 | 0.9133 | 0.9389   |
| 0.3861        | 3.0   | 555  | 0.2049          | 0.9185    | 0.9175 | 0.9180 | 0.9423   |
| 0.3861        | 4.0   | 740  | 0.2073          | 0.9183    | 0.9185 | 0.9184 | 0.9420   |
| 0.3861        | 5.0   | 925  | 0.2174          | 0.9150    | 0.9155 | 0.9153 | 0.9397   |
| 0.1487        | 6.0   | 1110 | 0.2227          | 0.9177    | 0.9185 | 0.9181 | 0.9415   |
| 0.1487        | 7.0   | 1295 | 0.2399          | 0.9149    | 0.9160 | 0.9155 | 0.9396   |
| 0.1487        | 8.0   | 1480 | 0.2504          | 0.9158    | 0.9163 | 0.9160 | 0.9400   |
| 0.0942        | 9.0   | 1665 | 0.2692          | 0.9141    | 0.9152 | 0.9146 | 0.9392   |
| 0.0942        | 10.0  | 1850 | 0.2782          | 0.9130    | 0.9153 | 0.9141 | 0.9388   |
| 0.0589        | 11.0  | 2035 | 0.2908          | 0.9131    | 0.9144 | 0.9138 | 0.9388   |
| 0.0589        | 12.0  | 2220 | 0.2940          | 0.9121    | 0.9136 | 0.9128 | 0.9377   |
| 0.0589        | 13.0  | 2405 | 0.3068          | 0.9117    | 0.9130 | 0.9123 | 0.9376   |
| 0.0407        | 14.0  | 2590 | 0.3107          | 0.9132    | 0.9148 | 0.9140 | 0.9387   |
| 0.0407        | 15.0  | 2775 | 0.3125          | 0.9120    | 0.9126 | 0.9123 | 0.9376   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "model_from_berturk_Feb_5_TrainTestSplit", "results": []}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

model\_from\_berturk\_Feb\_5\_TrainTestSplit
============================================


This model is a fine-tuned version of dbmdz/bert-base-turkish-cased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3125
* Precision: 0.9120
* Recall: 0.9126
* F1: 0.9123
* Accuracy: 0.9376


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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2