distilbert-base-uncased-finetuned-qqp
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: 0.0080
- Accuracy: 0.9991
- F1: 0.9983
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 19 | 0.3840 | 0.75 | 0.0 |
No log | 2.0 | 38 | 0.1577 | 0.9407 | 0.8882 |
No log | 3.0 | 57 | 0.0891 | 0.9588 | 0.9216 |
No log | 4.0 | 76 | 0.0495 | 0.9888 | 0.9774 |
No log | 5.0 | 95 | 0.0156 | 0.9974 | 0.9948 |
No log | 6.0 | 114 | 0.0107 | 0.9983 | 0.9966 |
No log | 7.0 | 133 | 0.0080 | 0.9991 | 0.9983 |
No log | 8.0 | 152 | 0.0074 | 0.9991 | 0.9983 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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