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# distilbert-base-multilingual-cased-ner-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: 0.1687
- Precision: 0.8684
- Recall: 0.8891
- F1: 0.8786
- Accuracy: 0.9693

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2009        | 1.0   | 572  | 0.1271          | 0.8074    | 0.8440 | 0.8253 | 0.9590   |
| 0.0951        | 2.0   | 1144 | 0.1069          | 0.8469    | 0.8768 | 0.8616 | 0.9671   |
| 0.063         | 3.0   | 1716 | 0.1136          | 0.8486    | 0.8783 | 0.8632 | 0.9680   |
| 0.0444        | 4.0   | 2288 | 0.1221          | 0.8506    | 0.8808 | 0.8654 | 0.9675   |
| 0.0303        | 5.0   | 2860 | 0.1389          | 0.8576    | 0.8823 | 0.8698 | 0.9677   |
| 0.0217        | 6.0   | 3432 | 0.1457          | 0.8683    | 0.8878 | 0.8779 | 0.9685   |
| 0.0157        | 7.0   | 4004 | 0.1542          | 0.8661    | 0.8873 | 0.8766 | 0.9692   |
| 0.0121        | 8.0   | 4576 | 0.1615          | 0.8730    | 0.8878 | 0.8803 | 0.9694   |
| 0.0094        | 9.0   | 5148 | 0.1675          | 0.8683    | 0.8883 | 0.8782 | 0.9688   |
| 0.0077        | 10.0  | 5720 | 0.1687          | 0.8684    | 0.8891 | 0.8786 | 0.9693   |


### 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": "distilbert-base-multilingual-cased-ner-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 

distilbert-base-multilingual-cased-ner-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: 0.1687
* Precision: 0.8684
* Recall: 0.8891
* F1: 0.8786
* Accuracy: 0.9693


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