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distilbert-base-uncased_fold_10_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: 1.6912
- F1: 0.7977
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 | 288 | 0.4002 | 0.8012 |
| 0.4056 | 2.0 | 576 | 0.4372 | 0.8075 |
| 0.4056 | 3.0 | 864 | 0.4720 | 0.8071 |
| 0.1958 | 4.0 | 1152 | 0.8156 | 0.7980 |
| 0.1958 | 5.0 | 1440 | 0.8633 | 0.8055 |
| 0.0847 | 6.0 | 1728 | 0.9761 | 0.8041 |
| 0.0356 | 7.0 | 2016 | 1.1816 | 0.7861 |
| 0.0356 | 8.0 | 2304 | 1.2251 | 0.7918 |
| 0.0215 | 9.0 | 2592 | 1.3423 | 0.7798 |
| 0.0215 | 10.0 | 2880 | 1.3888 | 0.7913 |
| 0.013 | 11.0 | 3168 | 1.2899 | 0.8040 |
| 0.013 | 12.0 | 3456 | 1.4247 | 0.8051 |
| 0.0049 | 13.0 | 3744 | 1.5436 | 0.7991 |
| 0.0061 | 14.0 | 4032 | 1.5762 | 0.7991 |
| 0.0061 | 15.0 | 4320 | 1.5461 | 0.7998 |
| 0.0054 | 16.0 | 4608 | 1.5622 | 0.8018 |
| 0.0054 | 17.0 | 4896 | 1.6658 | 0.7991 |
| 0.0021 | 18.0 | 5184 | 1.6765 | 0.7972 |
| 0.0021 | 19.0 | 5472 | 1.6864 | 0.7973 |
| 0.0052 | 20.0 | 5760 | 1.6303 | 0.8030 |
| 0.0029 | 21.0 | 6048 | 1.6631 | 0.7947 |
| 0.0029 | 22.0 | 6336 | 1.6571 | 0.8006 |
| 0.0027 | 23.0 | 6624 | 1.6729 | 0.7949 |
| 0.0027 | 24.0 | 6912 | 1.6931 | 0.7934 |
| 0.0001 | 25.0 | 7200 | 1.6912 | 0.7977 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
