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# de-bert-base-german-cased-finetuned

This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2858

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.3222        | 1.0   | 236  | 2.5917          |
| 2.7069        | 2.0   | 472  | 2.5008          |
| 2.5649        | 3.0   | 708  | 2.4164          |
| 2.4289        | 4.0   | 944  | 2.4542          |
| 2.3706        | 5.0   | 1180 | 2.3341          |
| 2.3106        | 6.0   | 1416 | 2.3479          |
| 2.2636        | 7.0   | 1652 | 2.2560          |
| 2.2039        | 8.0   | 1888 | 2.2804          |
| 2.1828        | 9.0   | 2124 | 2.2708          |
| 2.1414        | 10.0  | 2360 | 2.3298          |
| 2.1072        | 11.0  | 2596 | 2.2653          |
| 2.0809        | 12.0  | 2832 | 2.3277          |
| 2.0503        | 13.0  | 3068 | 2.2623          |
| 2.0231        | 14.0  | 3304 | 2.2312          |
| 2.039         | 15.0  | 3540 | 2.3196          |
| 1.9787        | 16.0  | 3776 | 2.2907          |
| 1.9726        | 17.0  | 4012 | 2.3083          |
| 1.9641        | 18.0  | 4248 | 2.3016          |
| 1.9501        | 19.0  | 4484 | 2.2497          |
| 1.948         | 20.0  | 4720 | 2.2211          |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "de-bert-base-german-cased-finetuned", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

de-bert-base-german-cased-finetuned
===================================


This model is a fine-tuned version of bert-base-german-cased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.2858


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: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.29.2
* 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: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-mit #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: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3