metadata
license: mit
base_model: flaubert/flaubert_base_cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: question_classification
results: []
question_classification
This model is a fine-tuned version of flaubert/flaubert_base_cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7638
- Accuracy: 0.8883
- F1: 0.8852
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: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 204 | 2.5153 | 0.1032 | 0.0609 |
| No log | 2.0 | 408 | 2.4600 | 0.4097 | 0.2689 |
| 2.5497 | 3.0 | 612 | 0.9799 | 0.5501 | 0.5544 |
| 2.5497 | 4.0 | 816 | 0.5244 | 0.7994 | 0.7992 |
| 0.8662 | 5.0 | 1020 | 0.5419 | 0.8281 | 0.8290 |
| 0.8662 | 6.0 | 1224 | 0.4333 | 0.8510 | 0.8520 |
| 0.8662 | 7.0 | 1428 | 0.4979 | 0.8711 | 0.8722 |
| 0.2222 | 8.0 | 1632 | 0.5494 | 0.8625 | 0.8635 |
| 0.2222 | 9.0 | 1836 | 0.6660 | 0.8739 | 0.8731 |
| 0.0445 | 10.0 | 2040 | 0.6472 | 0.8825 | 0.8810 |
| 0.0445 | 11.0 | 2244 | 0.7851 | 0.8940 | 0.8910 |
| 0.0445 | 12.0 | 2448 | 0.7119 | 0.8854 | 0.8851 |
| 0.0231 | 13.0 | 2652 | 0.8183 | 0.8883 | 0.8856 |
| 0.0231 | 14.0 | 2856 | 0.7676 | 0.8883 | 0.8852 |
| 0.0185 | 15.0 | 3060 | 0.7638 | 0.8883 | 0.8852 |
Framework versions
- Transformers 4.35.2
- Pytorch 1.13.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.2