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# bert-base-multilingual-uncased-mongolian-ner

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1378
- Precision: 0.9094
- Recall: 0.9227
- F1: 0.9160
- Accuracy: 0.9758

## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1758        | 1.0   | 477  | 0.1095          | 0.8593    | 0.8850 | 0.8720 | 0.9648   |
| 0.0863        | 2.0   | 954  | 0.1019          | 0.8855    | 0.9055 | 0.8954 | 0.9718   |
| 0.0601        | 3.0   | 1431 | 0.1063          | 0.8950    | 0.9086 | 0.9018 | 0.9724   |
| 0.04          | 4.0   | 1908 | 0.1050          | 0.8988    | 0.9171 | 0.9078 | 0.9745   |
| 0.0289        | 5.0   | 2385 | 0.1085          | 0.9003    | 0.9185 | 0.9093 | 0.9751   |
| 0.0203        | 6.0   | 2862 | 0.1134          | 0.9052    | 0.9193 | 0.9122 | 0.9747   |
| 0.0139        | 7.0   | 3339 | 0.1314          | 0.9089    | 0.9185 | 0.9137 | 0.9746   |
| 0.0102        | 8.0   | 3816 | 0.1306          | 0.9087    | 0.9199 | 0.9143 | 0.9748   |
| 0.0072        | 9.0   | 4293 | 0.1339          | 0.9091    | 0.9229 | 0.9160 | 0.9758   |
| 0.005         | 10.0  | 4770 | 0.1378          | 0.9094    | 0.9227 | 0.9160 | 0.9758   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"language": ["mn"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bert-base-multilingual-uncased-mongolian-ner", "results": []}]}
generated_from_trainer mn license:apache-2.0 region:us
TAGS
#generated_from_trainer #mn #license-apache-2.0 #region-us 

bert-base-multilingual-uncased-mongolian-ner
============================================


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


* Loss: 0.1378
* Precision: 0.9094
* Recall: 0.9227
* F1: 0.9160
* Accuracy: 0.9758


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: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#generated_from_trainer #mn #license-apache-2.0 #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3