---
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-multi-base-uncased-finetuned-pos-ky
  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. -->

# bert-multi-base-uncased-finetuned-pos-ky

This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0007
- Precision: 0.8230
- Recall: 0.8280
- F1: 0.8255
- Accuracy: 0.8850

## 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: 16
- 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   | 40   | 0.6248          | 0.6903    | 0.6708 | 0.6804 | 0.8350   |
| No log        | 2.0   | 80   | 0.4938          | 0.7555    | 0.7555 | 0.7555 | 0.8626   |
| No log        | 3.0   | 120  | 0.4931          | 0.7939    | 0.7948 | 0.7944 | 0.8764   |
| No log        | 4.0   | 160  | 0.4948          | 0.7776    | 0.8034 | 0.7903 | 0.8735   |
| No log        | 5.0   | 200  | 0.4744          | 0.8102    | 0.8231 | 0.8166 | 0.8850   |
| No log        | 6.0   | 240  | 0.5698          | 0.8042    | 0.8071 | 0.8056 | 0.8787   |
| No log        | 7.0   | 280  | 0.5787          | 0.7878    | 0.8120 | 0.7998 | 0.8758   |
| No log        | 8.0   | 320  | 0.6357          | 0.7841    | 0.8120 | 0.7978 | 0.8718   |
| No log        | 9.0   | 360  | 0.6359          | 0.8265    | 0.8366 | 0.8315 | 0.8879   |
| No log        | 10.0  | 400  | 0.6735          | 0.8048    | 0.8305 | 0.8174 | 0.8827   |
| No log        | 11.0  | 440  | 0.7243          | 0.8087    | 0.8206 | 0.8146 | 0.8804   |
| No log        | 12.0  | 480  | 0.7430          | 0.8133    | 0.8292 | 0.8212 | 0.8827   |
| 0.244         | 13.0  | 520  | 0.7097          | 0.8058    | 0.8206 | 0.8131 | 0.8810   |
| 0.244         | 14.0  | 560  | 0.7885          | 0.8152    | 0.8182 | 0.8167 | 0.8787   |
| 0.244         | 15.0  | 600  | 0.7925          | 0.8082    | 0.8231 | 0.8156 | 0.8827   |
| 0.244         | 16.0  | 640  | 0.7850          | 0.8270    | 0.8280 | 0.8275 | 0.8879   |
| 0.244         | 17.0  | 680  | 0.7881          | 0.8162    | 0.8292 | 0.8227 | 0.8850   |
| 0.244         | 18.0  | 720  | 0.8490          | 0.8168    | 0.8219 | 0.8194 | 0.8810   |
| 0.244         | 19.0  | 760  | 0.8470          | 0.8163    | 0.8243 | 0.8203 | 0.8815   |
| 0.244         | 20.0  | 800  | 0.8792          | 0.8007    | 0.8194 | 0.8100 | 0.8752   |
| 0.244         | 21.0  | 840  | 0.9056          | 0.8084    | 0.8243 | 0.8163 | 0.8769   |
| 0.244         | 22.0  | 880  | 0.9099          | 0.8152    | 0.8292 | 0.8222 | 0.8827   |
| 0.244         | 23.0  | 920  | 0.8455          | 0.8166    | 0.8317 | 0.8241 | 0.8844   |
| 0.244         | 24.0  | 960  | 0.9336          | 0.8140    | 0.8170 | 0.8155 | 0.8775   |
| 0.0193        | 25.0  | 1000 | 0.9462          | 0.8145    | 0.8145 | 0.8145 | 0.8787   |
| 0.0193        | 26.0  | 1040 | 0.9457          | 0.8200    | 0.8170 | 0.8185 | 0.8792   |
| 0.0193        | 27.0  | 1080 | 0.9312          | 0.8177    | 0.8268 | 0.8222 | 0.8798   |
| 0.0193        | 28.0  | 1120 | 0.9553          | 0.8235    | 0.8194 | 0.8214 | 0.8833   |
| 0.0193        | 29.0  | 1160 | 0.9450          | 0.8207    | 0.8268 | 0.8237 | 0.8821   |
| 0.0193        | 30.0  | 1200 | 0.9337          | 0.8335    | 0.8366 | 0.8351 | 0.8896   |
| 0.0193        | 31.0  | 1240 | 0.9476          | 0.8203    | 0.8354 | 0.8278 | 0.8861   |
| 0.0193        | 32.0  | 1280 | 0.9443          | 0.8182    | 0.8292 | 0.8237 | 0.8838   |
| 0.0193        | 33.0  | 1320 | 0.9713          | 0.8197    | 0.8268 | 0.8232 | 0.8844   |
| 0.0193        | 34.0  | 1360 | 0.9751          | 0.8210    | 0.8280 | 0.8245 | 0.8821   |
| 0.0193        | 35.0  | 1400 | 0.9850          | 0.8129    | 0.8219 | 0.8173 | 0.8815   |
| 0.0193        | 36.0  | 1440 | 0.9546          | 0.8182    | 0.8292 | 0.8237 | 0.8821   |
| 0.0193        | 37.0  | 1480 | 0.9713          | 0.8216    | 0.8317 | 0.8266 | 0.8844   |
| 0.0049        | 38.0  | 1520 | 0.9696          | 0.8234    | 0.8305 | 0.8269 | 0.8850   |
| 0.0049        | 39.0  | 1560 | 0.9722          | 0.8222    | 0.8354 | 0.8288 | 0.8861   |
| 0.0049        | 40.0  | 1600 | 0.9705          | 0.8273    | 0.8354 | 0.8313 | 0.8879   |
| 0.0049        | 41.0  | 1640 | 0.9777          | 0.8190    | 0.8280 | 0.8235 | 0.8838   |
| 0.0049        | 42.0  | 1680 | 0.9841          | 0.8167    | 0.8268 | 0.8217 | 0.8850   |
| 0.0049        | 43.0  | 1720 | 0.9799          | 0.8234    | 0.8305 | 0.8269 | 0.8873   |
| 0.0049        | 44.0  | 1760 | 0.9785          | 0.8248    | 0.8329 | 0.8289 | 0.8873   |
| 0.0049        | 45.0  | 1800 | 0.9863          | 0.8205    | 0.8256 | 0.8230 | 0.8856   |
| 0.0049        | 46.0  | 1840 | 0.9860          | 0.8278    | 0.8329 | 0.8304 | 0.8879   |
| 0.0049        | 47.0  | 1880 | 0.9870          | 0.8278    | 0.8329 | 0.8304 | 0.8879   |
| 0.0049        | 48.0  | 1920 | 0.9896          | 0.8278    | 0.8329 | 0.8304 | 0.8879   |
| 0.0049        | 49.0  | 1960 | 0.9997          | 0.8230    | 0.8280 | 0.8255 | 0.8850   |
| 0.0022        | 50.0  | 2000 | 1.0007          | 0.8230    | 0.8280 | 0.8255 | 0.8850   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.2.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1