metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_without_preprocessing_grid_search
results: []
distilBERT_without_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: 0.8740
- Precision: 0.8582
- Recall: 0.8441
- F1: 0.8491
- Accuracy: 0.8896
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: 5e-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 |
|---|---|---|---|---|---|---|---|
| 0.8195 | 1.0 | 514 | 0.5442 | 0.7965 | 0.8464 | 0.8071 | 0.8638 |
| 0.4249 | 2.0 | 1028 | 0.6446 | 0.8539 | 0.8236 | 0.8306 | 0.8769 |
| 0.3014 | 3.0 | 1542 | 0.6167 | 0.8484 | 0.8472 | 0.8463 | 0.8818 |
| 0.2268 | 4.0 | 2056 | 0.6262 | 0.8493 | 0.8594 | 0.8523 | 0.8896 |
| 0.1549 | 5.0 | 2570 | 0.6261 | 0.8443 | 0.8585 | 0.8501 | 0.8862 |
| 0.124 | 6.0 | 3084 | 0.8133 | 0.8566 | 0.8454 | 0.8503 | 0.8876 |
| 0.1057 | 7.0 | 3598 | 0.7241 | 0.8645 | 0.8596 | 0.8584 | 0.8925 |
| 0.0955 | 8.0 | 4112 | 0.8449 | 0.8532 | 0.8334 | 0.8421 | 0.8862 |
| 0.0744 | 9.0 | 4626 | 0.8140 | 0.8544 | 0.8536 | 0.8527 | 0.8901 |
| 0.0493 | 10.0 | 5140 | 0.8740 | 0.8582 | 0.8441 | 0.8491 | 0.8896 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3