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# test-distilbert-base-multilingual-cased

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: 0.1533
- Precision: 0.8783
- Recall: 0.9010
- F1: 0.8895
- Accuracy: 0.9721

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2124        | 1.0   | 477  | 0.1286          | 0.8065    | 0.8469 | 0.8262 | 0.9586   |
| 0.103         | 2.0   | 954  | 0.1113          | 0.8374    | 0.8772 | 0.8568 | 0.9663   |
| 0.0673        | 3.0   | 1431 | 0.1124          | 0.8480    | 0.8810 | 0.8641 | 0.9668   |
| 0.0474        | 4.0   | 1908 | 0.1165          | 0.8658    | 0.8922 | 0.8788 | 0.9710   |
| 0.0338        | 5.0   | 2385 | 0.1254          | 0.8664    | 0.8909 | 0.8785 | 0.9692   |
| 0.0236        | 6.0   | 2862 | 0.1349          | 0.8686    | 0.8954 | 0.8818 | 0.9707   |
| 0.018         | 7.0   | 3339 | 0.1428          | 0.8772    | 0.8991 | 0.8880 | 0.9715   |
| 0.0133        | 8.0   | 3816 | 0.1505          | 0.8739    | 0.8961 | 0.8849 | 0.9712   |
| 0.0106        | 9.0   | 4293 | 0.1529          | 0.8812    | 0.9012 | 0.8911 | 0.9720   |
| 0.0082        | 10.0  | 4770 | 0.1533          | 0.8783    | 0.9010 | 0.8895 | 0.9721   |


### Framework versions

- Transformers 4.28.0
- 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": "test-distilbert-base-multilingual-cased", "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 

test-distilbert-base-multilingual-cased
=======================================


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: 0.1533
* Precision: 0.8783
* Recall: 0.9010
* F1: 0.8895
* Accuracy: 0.9721


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 4.28.0
* 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 4.28.0
* 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 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3