metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: finetuned-DSCS24-mitre-distilbert-base-uncased-fill-mask
results: []
finetuned-DSCS24-mitre-distilbert-base-uncased-fill-mask
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: 2.0279
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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.7512 | 1.0 | 65 | 2.4057 |
| 2.3941 | 2.0 | 130 | 2.2818 |
| 2.2615 | 3.0 | 195 | 2.2630 |
| 2.2113 | 4.0 | 260 | 2.1359 |
| 2.1435 | 5.0 | 325 | 2.1022 |
| 2.0719 | 6.0 | 390 | 2.0463 |
| 2.0483 | 7.0 | 455 | 2.0830 |
| 2.0175 | 8.0 | 520 | 1.9946 |
| 1.9778 | 9.0 | 585 | 2.0038 |
| 1.9831 | 10.0 | 650 | 1.9502 |
| 1.8909 | 11.0 | 715 | 1.9914 |
| 1.9602 | 12.0 | 780 | 2.0588 |
| 1.9309 | 13.0 | 845 | 2.0038 |
| 1.9112 | 14.0 | 910 | 1.9957 |
| 1.9197 | 15.0 | 975 | 2.0338 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1