---
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: pos_tagger_3112
  results: []
---

<!-- 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. -->

# pos_tagger_3112

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: 0.5781
- Precision: 0.8885
- Recall: 0.8926
- F1: 0.8906
- Accuracy: 0.9222

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 244  | 0.2966          | 0.8889    | 0.8935 | 0.8912 | 0.9215   |
| No log        | 2.0   | 488  | 0.2884          | 0.8958    | 0.8969 | 0.8963 | 0.9258   |
| 0.3778        | 3.0   | 732  | 0.3138          | 0.8919    | 0.8913 | 0.8916 | 0.9224   |
| 0.3778        | 4.0   | 976  | 0.3086          | 0.8935    | 0.8960 | 0.8948 | 0.9252   |
| 0.1601        | 5.0   | 1220 | 0.3354          | 0.8897    | 0.8940 | 0.8919 | 0.9232   |
| 0.1601        | 6.0   | 1464 | 0.3486          | 0.8863    | 0.8911 | 0.8887 | 0.9212   |
| 0.1077        | 7.0   | 1708 | 0.3700          | 0.8899    | 0.8945 | 0.8922 | 0.9236   |
| 0.1077        | 8.0   | 1952 | 0.3920          | 0.8846    | 0.8905 | 0.8875 | 0.9207   |
| 0.0709        | 9.0   | 2196 | 0.4220          | 0.8860    | 0.8911 | 0.8885 | 0.9211   |
| 0.0709        | 10.0  | 2440 | 0.4467          | 0.8889    | 0.8934 | 0.8912 | 0.9226   |
| 0.0447        | 11.0  | 2684 | 0.4730          | 0.8834    | 0.8891 | 0.8862 | 0.9183   |
| 0.0447        | 12.0  | 2928 | 0.5008          | 0.8869    | 0.8921 | 0.8895 | 0.9217   |
| 0.0289        | 13.0  | 3172 | 0.5190          | 0.8866    | 0.8919 | 0.8892 | 0.9213   |
| 0.0289        | 14.0  | 3416 | 0.5384          | 0.8865    | 0.8904 | 0.8884 | 0.9204   |
| 0.0204        | 15.0  | 3660 | 0.5499          | 0.8852    | 0.8907 | 0.8879 | 0.9205   |
| 0.0204        | 16.0  | 3904 | 0.5564          | 0.8864    | 0.8923 | 0.8893 | 0.9213   |
| 0.015         | 17.0  | 4148 | 0.5688          | 0.8883    | 0.8920 | 0.8901 | 0.9220   |
| 0.015         | 18.0  | 4392 | 0.5740          | 0.8874    | 0.8927 | 0.8901 | 0.9213   |
| 0.0116        | 19.0  | 4636 | 0.5742          | 0.8879    | 0.8925 | 0.8902 | 0.9219   |
| 0.0116        | 20.0  | 4880 | 0.5781          | 0.8885    | 0.8926 | 0.8906 | 0.9222   |


### Framework versions

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