metadata
license: mit
base_model: bert-base-german-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Misinformation-Covid-Articles
results: []
Misinformation-Covid-Articles
This model is a fine-tuned version of bert-base-german-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1395
- Accuracy: 0.9840
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: 8
- eval_batch_size: 8
- 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 |
---|---|---|---|---|
0.1266 | 1.0 | 3609 | 0.1224 | 0.9703 |
0.0639 | 2.0 | 7218 | 0.1170 | 0.9735 |
0.0437 | 3.0 | 10827 | 0.1230 | 0.9808 |
0.0148 | 4.0 | 14436 | 0.1209 | 0.9832 |
0.0044 | 5.0 | 18045 | 0.1395 | 0.9840 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.12.0
- Tokenizers 0.13.3