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# bert-base-german-cased-finetuned-subj_v5_11Epoch

This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3467
- Precision: 0.8240
- Recall: 0.8287
- F1: 0.8263
- Accuracy: 0.9198

## 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: 11

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 32   | 0.3485          | 0.6992    | 0.7051 | 0.7021 | 0.8639   |
| No log        | 2.0   | 64   | 0.2679          | 0.7947    | 0.7612 | 0.7776 | 0.8994   |
| No log        | 3.0   | 96   | 0.2555          | 0.8073    | 0.8118 | 0.8095 | 0.9112   |
| No log        | 4.0   | 128  | 0.2591          | 0.8290    | 0.8034 | 0.8160 | 0.9132   |
| No log        | 5.0   | 160  | 0.2808          | 0.8450    | 0.8118 | 0.8281 | 0.9158   |
| No log        | 6.0   | 192  | 0.2953          | 0.8386    | 0.8174 | 0.8279 | 0.9172   |
| No log        | 7.0   | 224  | 0.3164          | 0.8347    | 0.8371 | 0.8359 | 0.9204   |
| No log        | 8.0   | 256  | 0.3267          | 0.8329    | 0.8258 | 0.8293 | 0.9178   |
| No log        | 9.0   | 288  | 0.3373          | 0.8268    | 0.8315 | 0.8291 | 0.9198   |
| No log        | 10.0  | 320  | 0.3450          | 0.8324    | 0.8230 | 0.8277 | 0.9211   |
| No log        | 11.0  | 352  | 0.3467          | 0.8240    | 0.8287 | 0.8263 | 0.9198   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bert-base-german-cased-finetuned-subj_v5_11Epoch", "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-finetuned-subj\_v5\_11Epoch
==================================================


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


* Loss: 0.3467
* Precision: 0.8240
* Recall: 0.8287
* F1: 0.8263
* Accuracy: 0.9198


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: 11


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6



### 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: 11 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6
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: 11 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6
passage: 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: 11### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6