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# wikineural-multilingual-ner-ner

This model is a fine-tuned version of [Babelscape/wikineural-multilingual-ner](https://huggingface.co/Babelscape/wikineural-multilingual-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0333
- Precision: 0.9718
- Recall: 0.9761
- F1: 0.9739
- Accuracy: 0.9937

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1605        | 1.0   | 477  | 0.0787          | 0.8892    | 0.9112 | 0.9001 | 0.9758   |
| 0.0816        | 2.0   | 954  | 0.0583          | 0.9188    | 0.9324 | 0.9256 | 0.9821   |
| 0.0533        | 3.0   | 1431 | 0.0474          | 0.9374    | 0.9494 | 0.9434 | 0.9865   |
| 0.0367        | 4.0   | 1908 | 0.0384          | 0.9555    | 0.9628 | 0.9591 | 0.9899   |
| 0.0272        | 5.0   | 2385 | 0.0363          | 0.9633    | 0.9667 | 0.9650 | 0.9910   |
| 0.0193        | 6.0   | 2862 | 0.0348          | 0.9664    | 0.9710 | 0.9687 | 0.9927   |
| 0.0142        | 7.0   | 3339 | 0.0328          | 0.9710    | 0.9746 | 0.9728 | 0.9931   |
| 0.0088        | 8.0   | 3816 | 0.0325          | 0.9731    | 0.9761 | 0.9746 | 0.9937   |
| 0.0069        | 9.0   | 4293 | 0.0332          | 0.9728    | 0.9766 | 0.9747 | 0.9939   |
| 0.0051        | 10.0  | 4770 | 0.0333          | 0.9718    | 0.9761 | 0.9739 | 0.9937   |


### Framework versions

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

{"language": ["mn"], "license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "wikineural-multilingual-ner-ner", "results": []}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer mn license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #mn #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 

wikineural-multilingual-ner-ner
===============================


This model is a fine-tuned version of Babelscape/wikineural-multilingual-ner on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0333
* Precision: 0.9718
* Recall: 0.9761
* F1: 0.9739
* Accuracy: 0.9937


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 #bert #token-classification #generated_from_trainer #mn #license-cc-by-nc-sa-4.0 #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