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distilbert-base-uncased-finetuned-osdg
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: 1.8193
- F1 Score: 0.7962
- Accuracy: 0.8434
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: 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Score | Accuracy |
|---|---|---|---|---|---|
| 0.3769 | 1.0 | 1017 | 0.8258 | 0.7729 | 0.8257 |
| 0.2759 | 2.0 | 2034 | 0.8364 | 0.7773 | 0.8262 |
| 0.1412 | 3.0 | 3051 | 1.0203 | 0.7833 | 0.8379 |
| 0.1423 | 4.0 | 4068 | 1.1603 | 0.7683 | 0.8224 |
| 0.0939 | 5.0 | 5085 | 1.3029 | 0.7843 | 0.8329 |
| 0.0757 | 6.0 | 6102 | 1.3562 | 0.7931 | 0.8379 |
| 0.0801 | 7.0 | 7119 | 1.2925 | 0.7840 | 0.8395 |
| 0.0311 | 8.0 | 8136 | 1.4632 | 0.7750 | 0.8318 |
| 0.0263 | 9.0 | 9153 | 1.5760 | 0.7843 | 0.8312 |
| 0.0196 | 10.0 | 10170 | 1.5689 | 0.7890 | 0.8417 |
| 0.0313 | 11.0 | 11187 | 1.6034 | 0.7909 | 0.8417 |
| 0.0007 | 12.0 | 12204 | 1.6725 | 0.7889 | 0.8406 |
| 0.0081 | 13.0 | 13221 | 1.6463 | 0.7911 | 0.8395 |
| 0.0061 | 14.0 | 14238 | 1.7730 | 0.7861 | 0.8345 |
| 0.003 | 15.0 | 15255 | 1.8001 | 0.7847 | 0.8379 |
| 0.0002 | 16.0 | 16272 | 1.7328 | 0.7912 | 0.8434 |
| 0.0 | 17.0 | 17289 | 1.7914 | 0.8011 | 0.8489 |
| 0.0009 | 18.0 | 18306 | 1.7772 | 0.7958 | 0.8456 |
| 0.0 | 19.0 | 19323 | 1.8028 | 0.7958 | 0.8434 |
| 0.0 | 20.0 | 20340 | 1.8193 | 0.7962 | 0.8434 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
