distilbert-base-uncased-finetuned-TeacherMomentsConfusion
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6691
- Accuracy: 0.7517
- Precision: 0.1790
- Recall: 0.2359
- F1: 0.2035
- Balanced Accuracy: 0.5339
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 | F1 | Balanced Accuracy |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 295 | 0.6717 | 0.8655 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6903 | 2.0 | 590 | 0.6691 | 0.7517 | 0.1790 | 0.2359 | 0.2035 | 0.5339 |
| 0.6903 | 3.0 | 885 | 0.7994 | 0.7076 | 0.1602 | 0.2769 | 0.2030 | 0.5257 |
| 0.5787 | 4.0 | 1180 | 1.0224 | 0.6317 | 0.1576 | 0.4 | 0.2261 | 0.5339 |
| 0.5787 | 5.0 | 1475 | 1.5546 | 0.7621 | 0.1528 | 0.1692 | 0.1606 | 0.5117 |
| 0.3142 | 6.0 | 1770 | 2.0188 | 0.7724 | 0.1271 | 0.1179 | 0.1223 | 0.4960 |
| 0.1212 | 7.0 | 2065 | 2.4508 | 0.8014 | 0.1157 | 0.0718 | 0.0886 | 0.4933 |
| 0.1212 | 8.0 | 2360 | 2.7545 | 0.8138 | 0.1287 | 0.0667 | 0.0878 | 0.4983 |
| 0.0543 | 9.0 | 2655 | 2.8085 | 0.7876 | 0.1258 | 0.0974 | 0.1098 | 0.4961 |
| 0.0543 | 10.0 | 2950 | 2.8602 | 0.7903 | 0.1342 | 0.1026 | 0.1163 | 0.4999 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3