metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_mergeddata_with_preprocessing_grid_search
results: []
distilBERT_mergeddata_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: 0.1825
- Precision: 0.9668
- Recall: 0.9672
- F1: 0.9669
- Accuracy: 0.9672
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: 3e-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 | 225 | 0.1820 | 0.9527 | 0.9500 | 0.9506 | 0.9511 |
| No log | 2.0 | 450 | 0.1582 | 0.9583 | 0.9584 | 0.9578 | 0.9583 |
| 0.3586 | 3.0 | 675 | 0.1369 | 0.9677 | 0.9678 | 0.9676 | 0.9678 |
| 0.3586 | 4.0 | 900 | 0.1371 | 0.9702 | 0.9706 | 0.9703 | 0.9706 |
| 0.0493 | 5.0 | 1125 | 0.1567 | 0.9686 | 0.9690 | 0.9687 | 0.9689 |
| 0.0493 | 6.0 | 1350 | 0.1622 | 0.9680 | 0.9685 | 0.9681 | 0.9683 |
| 0.0181 | 7.0 | 1575 | 0.1684 | 0.9640 | 0.9643 | 0.9640 | 0.9644 |
| 0.0181 | 8.0 | 1800 | 0.1717 | 0.9663 | 0.9666 | 0.9664 | 0.9667 |
| 0.0051 | 9.0 | 2025 | 0.1791 | 0.9674 | 0.9678 | 0.9675 | 0.9678 |
| 0.0051 | 10.0 | 2250 | 0.1825 | 0.9668 | 0.9672 | 0.9669 | 0.9672 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3