meister-mindmap-model-pytorch
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0163
- Accuracy: 0.9971
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7075 | 1.0 | 678 | 0.0548 | 0.9878 |
| 0.0613 | 2.0 | 1356 | 0.0163 | 0.9971 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.3
- Tokenizers 0.13.3
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Model tree for soymia/meister-mindmap-model-pytorch
Base model
distilbert/distilbert-base-uncased