metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_with_preprocessing_grid_search
results: []
distilBERT_with_preprocessing_grid_search
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: 0.7125
- Precision: 0.8239
- Recall: 0.8327
- F1: 0.8269
- Accuracy: 0.8581
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: 32
- eval_batch_size: 32
- 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 | 255 | 0.6963 | 0.7398 | 0.7965 | 0.7599 | 0.8292 |
| 0.934 | 2.0 | 510 | 0.5516 | 0.7593 | 0.8244 | 0.7846 | 0.8390 |
| 0.934 | 3.0 | 765 | 0.5481 | 0.7913 | 0.8211 | 0.8040 | 0.8513 |
| 0.3454 | 4.0 | 1020 | 0.5285 | 0.8089 | 0.8388 | 0.8216 | 0.8616 |
| 0.3454 | 5.0 | 1275 | 0.6033 | 0.8223 | 0.8361 | 0.8279 | 0.8635 |
| 0.1887 | 6.0 | 1530 | 0.6543 | 0.8231 | 0.8291 | 0.8250 | 0.8621 |
| 0.1887 | 7.0 | 1785 | 0.6787 | 0.8321 | 0.8373 | 0.8331 | 0.8655 |
| 0.1329 | 8.0 | 2040 | 0.6760 | 0.8144 | 0.8348 | 0.8225 | 0.8571 |
| 0.1329 | 9.0 | 2295 | 0.7171 | 0.8279 | 0.8348 | 0.8300 | 0.8616 |
| 0.0948 | 10.0 | 2550 | 0.7125 | 0.8239 | 0.8327 | 0.8269 | 0.8581 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3