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: 0.7803
- Precision: 0.8448
- Recall: 0.8438
- F1: 0.8437
- Accuracy: 0.8783
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 |
|---|---|---|---|---|---|---|---|
| 1.0001 | 1.0 | 514 | 0.6163 | 0.7620 | 0.8133 | 0.7790 | 0.8394 |
| 0.4832 | 2.0 | 1028 | 0.5556 | 0.8131 | 0.8284 | 0.8166 | 0.8623 |
| 0.3307 | 3.0 | 1542 | 0.5381 | 0.8168 | 0.8425 | 0.8254 | 0.8691 |
| 0.2429 | 4.0 | 2056 | 0.6014 | 0.8289 | 0.8455 | 0.8353 | 0.8720 |
| 0.1849 | 5.0 | 2570 | 0.6600 | 0.8367 | 0.8408 | 0.8375 | 0.8740 |
| 0.1564 | 6.0 | 3084 | 0.6724 | 0.8219 | 0.8491 | 0.8333 | 0.8696 |
| 0.1316 | 7.0 | 3598 | 0.7511 | 0.8536 | 0.8481 | 0.8501 | 0.8808 |
| 0.1037 | 8.0 | 4112 | 0.7284 | 0.8438 | 0.8494 | 0.8461 | 0.8798 |
| 0.0946 | 9.0 | 4626 | 0.7584 | 0.8452 | 0.8470 | 0.8457 | 0.8798 |
| 0.0731 | 10.0 | 5140 | 0.7803 | 0.8448 | 0.8438 | 0.8437 | 0.8783 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3