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# distilbert-base-german-europeana-cased-germeval_14

This model is a fine-tuned version of [dbmdz/distilbert-base-german-europeana-cased](https://huggingface.co/dbmdz/distilbert-base-german-europeana-cased) on the germeval_14 dataset.
It achieves the following results on the evaluation set:
- precision: 0.7437
- recall: 0.7571
- f1: 0.7504
- accuracy: 0.9541

## 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:
- num_train_epochs: 10
- train_batch_size: 8
- eval_batch_size: 8
- learning_rate: 1e-05
- weight_decay_rate: 0.01
- num_warmup_steps: 0
- fp16: True

### Framework versions

- Transformers 4.17.0
- Datasets 1.18.0
- Tokenizers 0.11.6

{"language": ["de"], "license": "mit", "datasets": ["germeval_14"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "distilbert-base-german-europeana-cased-germeval_14", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "germeval_14", "type": "germeval_14", "args": "default"}, "metrics": [{"type": "precision", "value": 0.7437097717963721, "name": "precision"}, {"type": "recall", "value": 0.7571485305798252, "name": "recall"}, {"type": "f1", "value": 0.7503689855357669, "name": "f1"}, {"type": "accuracy", "value": 0.9541357066185896, "name": "accuracy"}]}]}]}
transformers tf tensorboard distilbert token-classification de dataset:germeval_14 license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #tensorboard #distilbert #token-classification #de #dataset-germeval_14 #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 




# distilbert-base-german-europeana-cased-germeval_14

This model is a fine-tuned version of dbmdz/distilbert-base-german-europeana-cased on the germeval_14 dataset.
It achieves the following results on the evaluation set:
- precision: 0.7437
- recall: 0.7571
- f1: 0.7504
- accuracy: 0.9541

## 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:
- num_train_epochs: 10
- train_batch_size: 8
- eval_batch_size: 8
- learning_rate: 1e-05
- weight_decay_rate: 0.01
- num_warmup_steps: 0
- fp16: True

### Framework versions

- Transformers 4.17.0
- Datasets 1.18.0
- Tokenizers 0.11.6

# distilbert-base-german-europeana-cased-germeval_14

This model is a fine-tuned version of dbmdz/distilbert-base-german-europeana-cased on the germeval_14 dataset.
It achieves the following results on the evaluation set:
- precision: 0.7437
- recall: 0.7571
- f1: 0.7504
- accuracy: 0.9541 ## 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:
- num_train_epochs: 10
- train_batch_size: 8
- eval_batch_size: 8
- learning_rate: 1e-05
- weight_decay_rate: 0.01
- num_warmup_steps: 0
- fp16: True ### Framework versions

- Transformers 4.17.0
- Datasets 1.18.0
- Tokenizers 0.11.6
TAGS
#transformers #tf #tensorboard #distilbert #token-classification #de #dataset-germeval_14 #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 # distilbert-base-german-europeana-cased-germeval_14

This model is a fine-tuned version of dbmdz/distilbert-base-german-europeana-cased on the germeval_14 dataset.
It achieves the following results on the evaluation set:
- precision: 0.7437
- recall: 0.7571
- f1: 0.7504
- accuracy: 0.9541 ## 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:
- num_train_epochs: 10
- train_batch_size: 8
- eval_batch_size: 8
- learning_rate: 1e-05
- weight_decay_rate: 0.01
- num_warmup_steps: 0
- fp16: True ### Framework versions

- Transformers 4.17.0
- Datasets 1.18.0
- Tokenizers 0.11.6
passage: TAGS
#transformers #tf #tensorboard #distilbert #token-classification #de #dataset-germeval_14 #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
# distilbert-base-german-europeana-cased-germeval_14

This model is a fine-tuned version of dbmdz/distilbert-base-german-europeana-cased on the germeval_14 dataset.
It achieves the following results on the evaluation set:
- precision: 0.7437
- recall: 0.7571
- f1: 0.7504
- accuracy: 0.9541## 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:
- num_train_epochs: 10
- train_batch_size: 8
- eval_batch_size: 8
- learning_rate: 1e-05
- weight_decay_rate: 0.01
- num_warmup_steps: 0
- fp16: True### Framework versions

- Transformers 4.17.0
- Datasets 1.18.0
- Tokenizers 0.11.6