--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy base_model: distilbert-base-uncased model-index: - name: distilbert-base-uncased-finetuned-tagesschau-subcategories results: [] --- # distilbert-base-uncased-finetuned-tagesschau-subcategories This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7723 - Accuracy: 0.7267 ## 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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 0.4 | 30 | 1.3433 | 0.5667 | | No log | 0.8 | 60 | 1.0861 | 0.6933 | | No log | 1.2 | 90 | 0.9395 | 0.7067 | | No log | 1.6 | 120 | 0.8647 | 0.68 | | No log | 2.0 | 150 | 0.8018 | 0.72 | | No log | 2.4 | 180 | 0.7723 | 0.7267 | | No log | 2.8 | 210 | 0.7616 | 0.72 | | No log | 3.2 | 240 | 0.7348 | 0.7067 | | No log | 3.6 | 270 | 0.7747 | 0.72 | ### Framework versions - Transformers 4.25.1 - Pytorch 1.12.1+cu113 - Datasets 2.7.1 - Tokenizers 0.13.2