<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
distilbert-base-uncased-finetuned-scientific-eval
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: 0.1810
- Precision: 0.5820
- Recall: 0.6719
- F1: 0.6237
- Accuracy: 0.9483
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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 71 | 0.3580 | 0.3871 | 0.1893 | 0.2542 | 0.9068 |
| No log | 2.0 | 142 | 0.2235 | 0.5585 | 0.4669 | 0.5086 | 0.9332 |
| No log | 3.0 | 213 | 0.1870 | 0.6355 | 0.5994 | 0.6169 | 0.9456 |
| No log | 4.0 | 284 | 0.1857 | 0.5915 | 0.6120 | 0.6016 | 0.9474 |
| No log | 5.0 | 355 | 0.1810 | 0.5820 | 0.6719 | 0.6237 | 0.9483 |
| No log | 6.0 | 426 | 0.1969 | 0.6108 | 0.6435 | 0.6267 | 0.9505 |
| No log | 7.0 | 497 | 0.1914 | 0.5965 | 0.6530 | 0.6235 | 0.9513 |
| 0.1851 | 8.0 | 568 | 0.1964 | 0.6040 | 0.6593 | 0.6305 | 0.9517 |
| 0.1851 | 9.0 | 639 | 0.2026 | 0.6023 | 0.6593 | 0.6295 | 0.9517 |
| 0.1851 | 10.0 | 710 | 0.2027 | 0.6011 | 0.6751 | 0.6360 | 0.9508 |
Framework versions
- Transformers 4.27.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
