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# mongolian-distilbert-base-multilingual-cased-demo

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1370
- Precision: 0.8794
- Recall: 0.9055
- F1: 0.8923
- Accuracy: 0.9724

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2163        | 1.0   | 477  | 0.1387          | 0.7933    | 0.8434 | 0.8176 | 0.9560   |
| 0.1049        | 2.0   | 954  | 0.0989          | 0.8491    | 0.8840 | 0.8662 | 0.9688   |
| 0.0705        | 3.0   | 1431 | 0.0948          | 0.8598    | 0.8955 | 0.8773 | 0.9715   |
| 0.0476        | 4.0   | 1908 | 0.1065          | 0.8577    | 0.8969 | 0.8768 | 0.9701   |
| 0.0336        | 5.0   | 2385 | 0.1142          | 0.8703    | 0.8995 | 0.8847 | 0.9718   |
| 0.0252        | 6.0   | 2862 | 0.1225          | 0.8758    | 0.9023 | 0.8888 | 0.9716   |
| 0.018         | 7.0   | 3339 | 0.1256          | 0.8738    | 0.9022 | 0.8877 | 0.9716   |
| 0.0135        | 8.0   | 3816 | 0.1322          | 0.8807    | 0.9081 | 0.8942 | 0.9731   |
| 0.0103        | 9.0   | 4293 | 0.1367          | 0.8767    | 0.9043 | 0.8903 | 0.9720   |
| 0.0087        | 10.0  | 4770 | 0.1370          | 0.8794    | 0.9055 | 0.8923 | 0.9724   |


### 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-distilbert-base-multilingual-cased-demo", "results": []}]}
transformers pytorch tensorboard distilbert token-classification generated_from_trainer mn license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #mn #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

mongolian-distilbert-base-multilingual-cased-demo
=================================================


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


* Loss: 0.1370
* Precision: 0.8794
* Recall: 0.9055
* F1: 0.8923
* Accuracy: 0.9724


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 #distilbert #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