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: 0.6943
- Precision: 0.8467
- Recall: 0.8562
- F1: 0.8509
- Accuracy: 0.8793
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 | 257 | 0.5790 | 0.7659 | 0.8225 | 0.7875 | 0.8472 |
| 0.7473 | 2.0 | 514 | 0.5007 | 0.8115 | 0.8503 | 0.8264 | 0.8647 |
| 0.7473 | 3.0 | 771 | 0.4903 | 0.8007 | 0.8418 | 0.8174 | 0.8594 |
| 0.2608 | 4.0 | 1028 | 0.5370 | 0.8249 | 0.8491 | 0.8350 | 0.8657 |
| 0.2608 | 5.0 | 1285 | 0.6034 | 0.8424 | 0.8514 | 0.8455 | 0.8803 |
| 0.1543 | 6.0 | 1542 | 0.5988 | 0.8396 | 0.8565 | 0.8466 | 0.8788 |
| 0.1543 | 7.0 | 1799 | 0.6736 | 0.8486 | 0.8453 | 0.8458 | 0.8769 |
| 0.0981 | 8.0 | 2056 | 0.6476 | 0.8400 | 0.8605 | 0.8492 | 0.8788 |
| 0.0981 | 9.0 | 2313 | 0.6837 | 0.8443 | 0.8510 | 0.8469 | 0.8788 |
| 0.0713 | 10.0 | 2570 | 0.6943 | 0.8467 | 0.8562 | 0.8509 | 0.8793 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3