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# pos_tagger_3112_v3

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: 0.7728
- Precision: 0.8922
- Recall: 0.8955
- F1: 0.8938
- Accuracy: 0.9244

## 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: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 244   | 0.3040          | 0.8905    | 0.8924 | 0.8915 | 0.9215   |
| No log        | 2.0   | 488   | 0.2915          | 0.8981    | 0.9006 | 0.8994 | 0.9279   |
| 0.3896        | 3.0   | 732   | 0.3109          | 0.8933    | 0.8932 | 0.8933 | 0.9234   |
| 0.3896        | 4.0   | 976   | 0.3004          | 0.8954    | 0.8983 | 0.8969 | 0.9263   |
| 0.159         | 5.0   | 1220  | 0.3338          | 0.8929    | 0.8946 | 0.8937 | 0.9242   |
| 0.159         | 6.0   | 1464  | 0.3419          | 0.8914    | 0.8958 | 0.8936 | 0.9240   |
| 0.1038        | 7.0   | 1708  | 0.3840          | 0.8892    | 0.8930 | 0.8911 | 0.9223   |
| 0.1038        | 8.0   | 1952  | 0.3923          | 0.8857    | 0.8930 | 0.8894 | 0.9213   |
| 0.0629        | 9.0   | 2196  | 0.4441          | 0.8888    | 0.8914 | 0.8901 | 0.9213   |
| 0.0629        | 10.0  | 2440  | 0.4769          | 0.8886    | 0.8929 | 0.8908 | 0.9231   |
| 0.0357        | 11.0  | 2684  | 0.4846          | 0.8859    | 0.8913 | 0.8886 | 0.9199   |
| 0.0357        | 12.0  | 2928  | 0.5256          | 0.8877    | 0.8895 | 0.8886 | 0.9211   |
| 0.0212        | 13.0  | 3172  | 0.5554          | 0.8896    | 0.8900 | 0.8898 | 0.9219   |
| 0.0212        | 14.0  | 3416  | 0.5748          | 0.8870    | 0.8911 | 0.8890 | 0.9207   |
| 0.0143        | 15.0  | 3660  | 0.5988          | 0.8877    | 0.8916 | 0.8896 | 0.9220   |
| 0.0143        | 16.0  | 3904  | 0.6047          | 0.8874    | 0.8903 | 0.8888 | 0.9209   |
| 0.0098        | 17.0  | 4148  | 0.6161          | 0.8846    | 0.8914 | 0.8880 | 0.9199   |
| 0.0098        | 18.0  | 4392  | 0.6158          | 0.8883    | 0.8929 | 0.8906 | 0.9217   |
| 0.0072        | 19.0  | 4636  | 0.6216          | 0.8858    | 0.8928 | 0.8893 | 0.9209   |
| 0.0072        | 20.0  | 4880  | 0.6497          | 0.8892    | 0.8926 | 0.8909 | 0.9215   |
| 0.0058        | 21.0  | 5124  | 0.6698          | 0.8887    | 0.8919 | 0.8903 | 0.9216   |
| 0.0058        | 22.0  | 5368  | 0.6582          | 0.8858    | 0.8916 | 0.8887 | 0.9208   |
| 0.0046        | 23.0  | 5612  | 0.6915          | 0.8866    | 0.8925 | 0.8896 | 0.9212   |
| 0.0046        | 24.0  | 5856  | 0.6725          | 0.8898    | 0.8928 | 0.8913 | 0.9222   |
| 0.004         | 25.0  | 6100  | 0.6678          | 0.8912    | 0.8961 | 0.8936 | 0.9238   |
| 0.004         | 26.0  | 6344  | 0.6899          | 0.8891    | 0.8933 | 0.8912 | 0.9224   |
| 0.0034        | 27.0  | 6588  | 0.7082          | 0.8890    | 0.8922 | 0.8906 | 0.9215   |
| 0.0034        | 28.0  | 6832  | 0.7066          | 0.8903    | 0.8920 | 0.8911 | 0.9228   |
| 0.0026        | 29.0  | 7076  | 0.7243          | 0.8882    | 0.8938 | 0.8910 | 0.9228   |
| 0.0026        | 30.0  | 7320  | 0.7322          | 0.8891    | 0.8923 | 0.8907 | 0.9226   |
| 0.0023        | 31.0  | 7564  | 0.7292          | 0.8909    | 0.8930 | 0.8920 | 0.9230   |
| 0.0023        | 32.0  | 7808  | 0.7227          | 0.8922    | 0.8947 | 0.8934 | 0.9244   |
| 0.0027        | 33.0  | 8052  | 0.7231          | 0.8885    | 0.8922 | 0.8903 | 0.9222   |
| 0.0027        | 34.0  | 8296  | 0.7236          | 0.8907    | 0.8936 | 0.8922 | 0.9233   |
| 0.0019        | 35.0  | 8540  | 0.7313          | 0.8875    | 0.8895 | 0.8885 | 0.9214   |
| 0.0019        | 36.0  | 8784  | 0.7240          | 0.8902    | 0.8935 | 0.8919 | 0.9234   |
| 0.0017        | 37.0  | 9028  | 0.7364          | 0.8903    | 0.8939 | 0.8921 | 0.9233   |
| 0.0017        | 38.0  | 9272  | 0.7479          | 0.8896    | 0.8929 | 0.8913 | 0.9232   |
| 0.0013        | 39.0  | 9516  | 0.7511          | 0.8895    | 0.8937 | 0.8916 | 0.9230   |
| 0.0013        | 40.0  | 9760  | 0.7689          | 0.8896    | 0.8948 | 0.8922 | 0.9234   |
| 0.001         | 41.0  | 10004 | 0.7597          | 0.8909    | 0.8958 | 0.8933 | 0.9238   |
| 0.001         | 42.0  | 10248 | 0.7581          | 0.8897    | 0.8929 | 0.8913 | 0.9230   |
| 0.001         | 43.0  | 10492 | 0.7512          | 0.8919    | 0.8952 | 0.8935 | 0.9244   |
| 0.0012        | 44.0  | 10736 | 0.7622          | 0.8921    | 0.8957 | 0.8939 | 0.9244   |
| 0.0012        | 45.0  | 10980 | 0.7707          | 0.8907    | 0.8952 | 0.8930 | 0.9237   |
| 0.001         | 46.0  | 11224 | 0.7700          | 0.8922    | 0.8963 | 0.8942 | 0.9244   |
| 0.001         | 47.0  | 11468 | 0.7742          | 0.8895    | 0.8938 | 0.8916 | 0.9231   |
| 0.0009        | 48.0  | 11712 | 0.7753          | 0.8911    | 0.8945 | 0.8928 | 0.9239   |
| 0.0009        | 49.0  | 11956 | 0.7746          | 0.8909    | 0.8944 | 0.8927 | 0.9236   |
| 0.0008        | 50.0  | 12200 | 0.7728          | 0.8922    | 0.8955 | 0.8938 | 0.9244   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "dbmdz/bert-base-turkish-cased", "model-index": [{"name": "pos_tagger_3112_v3", "results": []}]}
transformers tensorboard safetensors bert token-classification generated_from_trainer base_model:dbmdz/bert-base-turkish-cased license:mit autotrain_compatible endpoints_compatible region:us