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| license: mit | |
| base_model: dbmdz/bert-base-german-uncased | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: class_classificator_results | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # class_classificator_results | |
| This model is a fine-tuned version of [dbmdz/bert-base-german-uncased](https://huggingface.co/dbmdz/bert-base-german-uncased) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.7191 | |
| - Precision: 0.9280 | |
| - Recall: 0.9280 | |
| - F1: 0.9280 | |
| - Accuracy: 0.9280 | |
| ## 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 | |
| - lr_scheduler_warmup_steps: 500 | |
| - num_epochs: 6 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| | 1.3487 | 1.0 | 2527 | 1.1844 | 0.8355 | 0.8355 | 0.8355 | 0.8355 | | |
| | 0.9081 | 2.0 | 5054 | 0.9115 | 0.8897 | 0.8897 | 0.8897 | 0.8897 | | |
| | 0.6327 | 3.0 | 7581 | 0.7873 | 0.9038 | 0.9038 | 0.9038 | 0.9038 | | |
| | 0.3874 | 4.0 | 10108 | 0.7599 | 0.9196 | 0.9196 | 0.9196 | 0.9196 | | |
| | 0.2643 | 5.0 | 12635 | 0.7191 | 0.9280 | 0.9280 | 0.9280 | 0.9280 | | |
| | 0.2146 | 6.0 | 15162 | 0.7315 | 0.9300 | 0.9300 | 0.9300 | 0.9300 | | |
| ### Framework versions | |
| - Transformers 4.41.2 | |
| - Pytorch 2.0.1+cu117 | |
| - Datasets 2.20.0 | |
| - Tokenizers 0.19.1 | |