results
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5997
- Accuracy: 0.8676
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7901 | 1.0 | 506 | 0.7990 | 0.8387 |
| 0.6078 | 2.0 | 1012 | 0.6753 | 0.8587 |
| 0.4831 | 3.0 | 1518 | 0.6152 | 0.8699 |
| 0.4025 | 4.0 | 2024 | 0.6079 | 0.8665 |
| 0.3813 | 5.0 | 2530 | 0.5997 | 0.8676 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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Model tree for dejua/results
Base model
distilbert/distilbert-base-uncased