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distilbert-base-uncased-PINA-dfnew-insyaallah
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: 0.2680
- Accuracy: 0.9431
- Precision: 0.8480
- Recall: 0.8258
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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
---|---|---|---|---|---|---|
1.1591 | 1.0 | 1436 | 0.4581 | 0.8945 | 0.7871 | 0.7185 |
0.3058 | 2.0 | 2872 | 0.2901 | 0.9349 | 0.8307 | 0.8157 |
0.1623 | 3.0 | 4308 | 0.2680 | 0.9431 | 0.8480 | 0.8258 |
0.0936 | 4.0 | 5744 | 0.2942 | 0.9474 | 0.8758 | 0.8415 |
0.0562 | 5.0 | 7180 | 0.2681 | 0.9535 | 0.8730 | 0.8527 |
0.034 | 6.0 | 8616 | 0.3010 | 0.9504 | 0.8761 | 0.8474 |
0.0193 | 7.0 | 10052 | 0.2971 | 0.9532 | 0.8643 | 0.8507 |
0.0115 | 8.0 | 11488 | 0.3139 | 0.9519 | 0.8640 | 0.8489 |
0.0078 | 9.0 | 12924 | 0.3056 | 0.9551 | 0.8649 | 0.8529 |
0.0056 | 10.0 | 14360 | 0.3062 | 0.9549 | 0.8636 | 0.8531 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3