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Misinformation-Covid-Warmupbert-base-german-cased
Ghunghru/Misinformation-Covid-Warmupbert-base-german-cased
Misinformation-Covid-Warmupbert-base-german-cased is a text classification model from Ghunghru. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Jan 15, 2024
- Updated
- Jan 15, 2024
- SHA
- cf4828ba
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
Misinformation-Covid-Warmupbert-base-german-cased
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: 0.6650
- Accuracy: 0.8977
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: 0.0002
- 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
- lr_scheduler_warmup_steps: 50
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.863 | 1.0 | 216 | 0.6858 | 0.8977 |
| 0.7632 | 2.0 | 432 | 0.6650 | 0.8977 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Jan 15, 2024
- Updated
- Jan 15, 2024