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# mongolian-bert-base-multilingual-cased-demo

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: 0.1375
- Precision: 0.9051
- Recall: 0.9203
- F1: 0.9126
- Accuracy: 0.9775

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1747        | 1.0   | 477  | 0.1069          | 0.8431    | 0.8768 | 0.8596 | 0.9663   |
| 0.0845        | 2.0   | 954  | 0.0870          | 0.8887    | 0.9001 | 0.8944 | 0.9748   |
| 0.0591        | 3.0   | 1431 | 0.0987          | 0.8914    | 0.9059 | 0.8986 | 0.9730   |
| 0.0388        | 4.0   | 1908 | 0.1065          | 0.8928    | 0.9093 | 0.9010 | 0.9733   |
| 0.0278        | 5.0   | 2385 | 0.1173          | 0.8969    | 0.9150 | 0.9059 | 0.9760   |
| 0.0196        | 6.0   | 2862 | 0.1215          | 0.9050    | 0.9169 | 0.9109 | 0.9765   |
| 0.0142        | 7.0   | 3339 | 0.1229          | 0.9063    | 0.9183 | 0.9123 | 0.9771   |
| 0.01          | 8.0   | 3816 | 0.1283          | 0.9017    | 0.9159 | 0.9087 | 0.9767   |
| 0.0074        | 9.0   | 4293 | 0.1319          | 0.9066    | 0.9201 | 0.9133 | 0.9776   |
| 0.0051        | 10.0  | 4770 | 0.1375          | 0.9051    | 0.9203 | 0.9126 | 0.9775   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+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": "mongolian-bert-base-multilingual-cased-demo", "results": []}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer mn license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #mn #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

mongolian-bert-base-multilingual-cased-demo
===========================================


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: 0.1375
* Precision: 0.9051
* Recall: 0.9203
* F1: 0.9126
* Accuracy: 0.9775


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 4.29.2
* Pytorch 2.0.1+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 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #mn #license-apache-2.0 #autotrain_compatible #endpoints_compatible #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 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3