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# bert-base-german-cased-noisy-pretrain-fine-tuned_v1.1

This model is a fine-tuned version of [tbosse/bert-base-german-cased-finetuned-subj_preTrained_with_noisyData_v1.1](https://huggingface.co/tbosse/bert-base-german-cased-finetuned-subj_preTrained_with_noisyData_v1.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2742
- Precision: 0.8072
- Recall: 0.7657
- F1: 0.7859
- Accuracy: 0.9217

## 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 33   | 0.3112          | 0.7601    | 0.5886 | 0.6634 | 0.8773   |
| No log        | 2.0   | 66   | 0.2539          | 0.7706    | 0.72   | 0.7445 | 0.9038   |
| No log        | 3.0   | 99   | 0.2416          | 0.7755    | 0.76   | 0.7677 | 0.9130   |
| No log        | 4.0   | 132  | 0.2536          | 0.8190    | 0.7371 | 0.7759 | 0.9165   |
| No log        | 5.0   | 165  | 0.2644          | 0.7982    | 0.7457 | 0.7710 | 0.9176   |
| No log        | 6.0   | 198  | 0.2735          | 0.8142    | 0.7514 | 0.7816 | 0.9205   |
| No log        | 7.0   | 231  | 0.2742          | 0.8072    | 0.7657 | 0.7859 | 0.9217   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bert-base-german-cased-noisy-pretrain-fine-tuned_v1.1", "results": []}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

bert-base-german-cased-noisy-pretrain-fine-tuned\_v1.1
======================================================


This model is a fine-tuned version of tbosse/bert-base-german-cased-finetuned-subj\_preTrained\_with\_noisyData\_v1.1 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2742
* Precision: 0.8072
* Recall: 0.7657
* F1: 0.7859
* Accuracy: 0.9217


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: 7


### Training results



### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1



### 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: 7 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #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: 7 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #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: 7### Training results### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1