distilbert-base-uncased-finetuned-qqp
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: 0.4818
- Accuracy: 0.9061
- F1: 0.8741
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.2733 | 1.0 | 22741 | 0.2698 | 0.8826 | 0.8502 |
0.2296 | 2.0 | 45482 | 0.2598 | 0.8976 | 0.8629 |
0.1678 | 3.0 | 68223 | 0.3375 | 0.9010 | 0.8689 |
0.1177 | 4.0 | 90964 | 0.4048 | 0.9046 | 0.8721 |
0.086 | 5.0 | 113705 | 0.4818 | 0.9061 | 0.8741 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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