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distilbert-base-uncased_fold_12_binary_v1
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: 1.7046
- F1: 0.8165
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: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 290 | 0.4165 | 0.7983 |
| 0.4052 | 2.0 | 580 | 0.4005 | 0.8213 |
| 0.4052 | 3.0 | 870 | 0.6003 | 0.8078 |
| 0.1906 | 4.0 | 1160 | 0.8181 | 0.7945 |
| 0.1906 | 5.0 | 1450 | 0.7775 | 0.7955 |
| 0.0853 | 6.0 | 1740 | 1.0667 | 0.7912 |
| 0.0407 | 7.0 | 2030 | 1.2061 | 0.7907 |
| 0.0407 | 8.0 | 2320 | 1.2522 | 0.8011 |
| 0.0145 | 9.0 | 2610 | 1.3073 | 0.8110 |
| 0.0145 | 10.0 | 2900 | 1.4895 | 0.7994 |
| 0.015 | 11.0 | 3190 | 1.4568 | 0.8082 |
| 0.015 | 12.0 | 3480 | 1.4883 | 0.8058 |
| 0.005 | 13.0 | 3770 | 1.4334 | 0.8217 |
| 0.0026 | 14.0 | 4060 | 1.5032 | 0.8255 |
| 0.0026 | 15.0 | 4350 | 1.5694 | 0.8193 |
| 0.0062 | 16.0 | 4640 | 1.6058 | 0.8105 |
| 0.0062 | 17.0 | 4930 | 1.7390 | 0.8058 |
| 0.0051 | 18.0 | 5220 | 1.6942 | 0.8100 |
| 0.0012 | 19.0 | 5510 | 1.6891 | 0.8151 |
| 0.0012 | 20.0 | 5800 | 1.6961 | 0.8132 |
| 0.0007 | 21.0 | 6090 | 1.6793 | 0.8168 |
| 0.0007 | 22.0 | 6380 | 1.7542 | 0.8077 |
| 0.0027 | 23.0 | 6670 | 1.6869 | 0.8203 |
| 0.0027 | 24.0 | 6960 | 1.7006 | 0.8194 |
| 0.0028 | 25.0 | 7250 | 1.7046 | 0.8165 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
