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# distilbert-base-german-cased-finetuned-ner

This model is a fine-tuned version of [distilbert-base-german-cased](https://huggingface.co/distilbert-base-german-cased) on the wikiann dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1871
- Precision: 0.8401
- Recall: 0.8744
- F1: 0.8569
- Accuracy: 0.9548

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1785        | 1.0   | 2500 | 0.1728          | 0.8134    | 0.8414 | 0.8271 | 0.9490   |
| 0.1252        | 2.0   | 5000 | 0.1743          | 0.8434    | 0.8659 | 0.8545 | 0.9545   |
| 0.0867        | 3.0   | 7500 | 0.1871          | 0.8401    | 0.8744 | 0.8569 | 0.9548   |


### Framework versions

- Transformers 4.27.3
- Pytorch 2.0.0+cu118
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["wikiann"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "distilbert-base-german-cased-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "wikiann", "type": "wikiann", "config": "de", "split": "validation", "args": "de"}, "metrics": [{"type": "precision", "value": 0.8400889939511924, "name": "Precision"}, {"type": "recall", "value": 0.8744391373570705, "name": "Recall"}, {"type": "f1", "value": 0.8569199673770433, "name": "F1"}, {"type": "accuracy", "value": 0.9548258089954094, "name": "Accuracy"}]}]}]}
transformers pytorch distilbert token-classification generated_from_trainer dataset:wikiann license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #token-classification #generated_from_trainer #dataset-wikiann #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

distilbert-base-german-cased-finetuned-ner
==========================================


This model is a fine-tuned version of distilbert-base-german-cased on the wikiann dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1871
* Precision: 0.8401
* Recall: 0.8744
* F1: 0.8569
* Accuracy: 0.9548


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: 8
* eval\_batch\_size: 8
* 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 4.27.3
* Pytorch 2.0.0+cu118
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* 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 4.27.3
* Pytorch 2.0.0+cu118
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #distilbert #token-classification #generated_from_trainer #dataset-wikiann #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* 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 4.27.3
* Pytorch 2.0.0+cu118
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #distilbert #token-classification #generated_from_trainer #dataset-wikiann #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* 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 4.27.3
* Pytorch 2.0.0+cu118
* Datasets 2.10.1
* Tokenizers 0.13.2