|
--- |
|
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: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# distilBERT_without_preprocessing_grid_search |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7927 |
|
- Precision: 0.8512 |
|
- Recall: 0.8478 |
|
- F1: 0.8484 |
|
- Accuracy: 0.8842 |
|
|
|
## 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: 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 | 0.5177 | 0.7547 | 0.8422 | 0.7806 | 0.8444 | |
|
| 0.6866 | 2.0 | 514 | 0.4727 | 0.8301 | 0.8543 | 0.8372 | 0.8794 | |
|
| 0.6866 | 3.0 | 771 | 0.5257 | 0.8261 | 0.8508 | 0.8347 | 0.8779 | |
|
| 0.2332 | 4.0 | 1028 | 0.5768 | 0.8254 | 0.8651 | 0.8423 | 0.8818 | |
|
| 0.2332 | 5.0 | 1285 | 0.6244 | 0.8405 | 0.8529 | 0.8462 | 0.8852 | |
|
| 0.1201 | 6.0 | 1542 | 0.7367 | 0.8520 | 0.8507 | 0.8505 | 0.8838 | |
|
| 0.1201 | 7.0 | 1799 | 0.6644 | 0.8419 | 0.8607 | 0.8498 | 0.8833 | |
|
| 0.0848 | 8.0 | 2056 | 0.7632 | 0.8522 | 0.8433 | 0.8465 | 0.8833 | |
|
| 0.0848 | 9.0 | 2313 | 0.7510 | 0.8515 | 0.8569 | 0.8532 | 0.8867 | |
|
| 0.0517 | 10.0 | 2570 | 0.7927 | 0.8512 | 0.8478 | 0.8484 | 0.8842 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.4 |
|
- Tokenizers 0.13.3 |
|
|
