metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_bio_pv_superset
results: []
distilBERT_bio_pv_superset
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: 0.2328
- Precision: 0.5462
- Recall: 0.5325
- F1: 0.5393
- Accuracy: 0.9495
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 |
|---|---|---|---|---|---|---|---|
| 0.0964 | 1.0 | 5467 | 0.1593 | 0.4625 | 0.3682 | 0.4100 | 0.9416 |
| 0.1918 | 2.0 | 10934 | 0.1541 | 0.4796 | 0.4658 | 0.4726 | 0.9436 |
| 0.0394 | 3.0 | 16401 | 0.1508 | 0.5349 | 0.4744 | 0.5028 | 0.9482 |
| 0.1207 | 4.0 | 21868 | 0.1615 | 0.5422 | 0.4953 | 0.5177 | 0.9490 |
| 0.0221 | 5.0 | 27335 | 0.1827 | 0.5377 | 0.5018 | 0.5191 | 0.9487 |
| 0.0629 | 6.0 | 32802 | 0.1874 | 0.5479 | 0.5130 | 0.5299 | 0.9493 |
| 0.0173 | 7.0 | 38269 | 0.2025 | 0.5388 | 0.5323 | 0.5356 | 0.9488 |
| 0.2603 | 8.0 | 43736 | 0.2148 | 0.5437 | 0.5397 | 0.5417 | 0.9493 |
| 0.0378 | 9.0 | 49203 | 0.2323 | 0.5430 | 0.5194 | 0.5310 | 0.9489 |
| 0.031 | 10.0 | 54670 | 0.2328 | 0.5462 | 0.5325 | 0.5393 | 0.9495 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1