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# gunghio/distilbert-base-multilingual-cased-finetuned-conll2003-ner

This model was trained from scratch on an conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0388
- Precision: 0.9360
- Recall: 0.9458
- F1: 0.9409
- Accuracy: 0.9902

## Model description

It is based on distilbert-base-multilingual-cased

## Intended uses & limitations

More information needed

## Training and evaluation data

Training dataset: [conll2003](https://huggingface.co/datasets/conll2003)

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1653        | 1.0   | 878  | 0.0465          | 0.9267    | 0.9300 | 0.9283 | 0.9883   |
| 0.0322        | 2.0   | 1756 | 0.0404          | 0.9360    | 0.9431 | 0.9396 | 0.9897   |
| 0.0185        | 3.0   | 2634 | 0.0388          | 0.9360    | 0.9458 | 0.9409 | 0.9902   |


### Framework versions

- Transformers 4.6.1
- Pytorch 1.8.1+cu101
- Datasets 1.6.2
- Tokenizers 0.10.2

{"language": ["en", "de", "nl", "es", "multilingual"], "datasets": ["conll2003"], "metrics": [{"precision": 0.936}, {"recall": 0.9458}, {"f1": 0.9409}, {"accuracy": 0.9902}], "model-index": [{"name": "gunghio/distilbert-base-multilingual-cased-finetuned-conll2003-ner", "results": [{"task": {"type": "ner", "name": "Named Entity Recognition"}, "dataset": {"name": "ConLL 2003", "type": "conll2003"}, "metrics": [{"type": "f1-score", "value": 0.9409}]}]}]}
transformers pytorch distilbert token-classification en de nl es multilingual dataset:conll2003 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #token-classification #en #de #nl #es #multilingual #dataset-conll2003 #model-index #autotrain_compatible #endpoints_compatible #region-us 

gunghio/distilbert-base-multilingual-cased-finetuned-conll2003-ner
==================================================================


This model was trained from scratch on an conll2003 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0388
* Precision: 0.9360
* Recall: 0.9458
* F1: 0.9409
* Accuracy: 0.9902


Model description
-----------------


It is based on distilbert-base-multilingual-cased


Intended uses & limitations
---------------------------


More information needed


Training and evaluation data
----------------------------


Training dataset: conll2003


Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3


### Training results



### Framework versions


* Transformers 4.6.1
* Pytorch 1.8.1+cu101
* Datasets 1.6.2
* Tokenizers 0.10.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.6.1
* Pytorch 1.8.1+cu101
* Datasets 1.6.2
* Tokenizers 0.10.2
TAGS
#transformers #pytorch #distilbert #token-classification #en #de #nl #es #multilingual #dataset-conll2003 #model-index #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: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.6.1
* Pytorch 1.8.1+cu101
* Datasets 1.6.2
* Tokenizers 0.10.2
passage: TAGS
#transformers #pytorch #distilbert #token-classification #en #de #nl #es #multilingual #dataset-conll2003 #model-index #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: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3### Training results### Framework versions


* Transformers 4.6.1
* Pytorch 1.8.1+cu101
* Datasets 1.6.2
* Tokenizers 0.10.2