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# output-model

This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on the hyperinfer/justizscrap_verkehrsunfall dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9121
- Accuracy: 0.7842

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 24
- total_train_batch_size: 768
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["hyperinfer/justizscrap_verkehrsunfall"], "metrics": ["accuracy"], "base_model": "bert-base-german-cased", "model-index": [{"name": "output-model", "results": [{"task": {"type": "fill-mask", "name": "Masked Language Modeling"}, "dataset": {"name": "hyperinfer/justizscrap_verkehrsunfall", "type": "hyperinfer/justizscrap_verkehrsunfall"}, "metrics": [{"type": "accuracy", "value": 0.784188299590113, "name": "Accuracy"}]}]}]}
transformers pytorch bert fill-mask generated_from_trainer dataset:hyperinfer/justizscrap_verkehrsunfall base_model:bert-base-german-cased license:mit model-index autotrain_compatible endpoints_compatible region:us