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: 0.7065
- Precision: 0.8418
- Recall: 0.8521
- F1: 0.8453
- Accuracy: 0.8838
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 | 257 | 0.5948 | 0.7470 | 0.8351 | 0.7753 | 0.8375 |
| 0.8584 | 2.0 | 514 | 0.5402 | 0.7946 | 0.8405 | 0.8048 | 0.8643 |
| 0.8584 | 3.0 | 771 | 0.5362 | 0.8012 | 0.8425 | 0.8164 | 0.8682 |
| 0.3181 | 4.0 | 1028 | 0.5224 | 0.8062 | 0.8622 | 0.8290 | 0.875 |
| 0.3181 | 5.0 | 1285 | 0.5766 | 0.8234 | 0.8514 | 0.8353 | 0.8769 |
| 0.1767 | 6.0 | 1542 | 0.6231 | 0.8229 | 0.8531 | 0.8363 | 0.8755 |
| 0.1767 | 7.0 | 1799 | 0.6359 | 0.8370 | 0.8576 | 0.8456 | 0.8847 |
| 0.1231 | 8.0 | 2056 | 0.6849 | 0.8391 | 0.8538 | 0.8452 | 0.8823 |
| 0.1231 | 9.0 | 2313 | 0.6961 | 0.8453 | 0.8450 | 0.8431 | 0.8823 |
| 0.0862 | 10.0 | 2570 | 0.7065 | 0.8418 | 0.8521 | 0.8453 | 0.8838 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3