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naadedei-Finetuned-distilbert-model
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: 0.6769
- Accuracy: 0.7388
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: 1e-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 |
---|---|---|---|---|
0.8572 | 0.5 | 500 | 0.7690 | 0.6962 |
0.7582 | 1.0 | 1000 | 0.7043 | 0.7333 |
0.6506 | 1.5 | 1500 | 0.7189 | 0.7393 |
0.6615 | 2.0 | 2000 | 0.6769 | 0.7388 |
0.5304 | 2.51 | 2500 | 0.7274 | 0.7393 |
0.5294 | 3.01 | 3000 | 0.7291 | 0.7419 |
0.4495 | 3.51 | 3500 | 0.7946 | 0.7439 |
0.4372 | 4.01 | 4000 | 0.8052 | 0.7459 |
0.3863 | 4.51 | 4500 | 0.8386 | 0.7414 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1