---
license: mit
base_model: flaubert/flaubert_base_cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: question_classification
  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. -->

# question_classification

This model is a fine-tuned version of [flaubert/flaubert_base_cased](https://huggingface.co/flaubert/flaubert_base_cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0442
- Accuracy: 0.9054
- F1: 0.9045

## 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: 35

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 204  | 1.2496          | 0.6132   | 0.6098 |
| No log        | 2.0   | 408  | 0.7790          | 0.7249   | 0.7231 |
| 1.2508        | 3.0   | 612  | 0.6412          | 0.8023   | 0.8038 |
| 1.2508        | 4.0   | 816  | 0.5420          | 0.8682   | 0.8681 |
| 0.318         | 5.0   | 1020 | 0.7027          | 0.8453   | 0.8428 |
| 0.318         | 6.0   | 1224 | 0.6174          | 0.8625   | 0.8629 |
| 0.318         | 7.0   | 1428 | 0.6363          | 0.8768   | 0.8772 |
| 0.121         | 8.0   | 1632 | 0.7726          | 0.8682   | 0.8695 |
| 0.121         | 9.0   | 1836 | 1.0105          | 0.8739   | 0.8734 |
| 0.043         | 10.0  | 2040 | 0.9210          | 0.8854   | 0.8855 |
| 0.043         | 11.0  | 2244 | 0.9544          | 0.8825   | 0.8794 |
| 0.043         | 12.0  | 2448 | 0.8467          | 0.8825   | 0.8825 |
| 0.0287        | 13.0  | 2652 | 0.8958          | 0.8968   | 0.8963 |
| 0.0287        | 14.0  | 2856 | 1.0431          | 0.8854   | 0.8844 |
| 0.0244        | 15.0  | 3060 | 1.0537          | 0.8854   | 0.8844 |
| 0.0244        | 16.0  | 3264 | 0.8005          | 0.9054   | 0.9052 |
| 0.0244        | 17.0  | 3468 | 0.9819          | 0.8883   | 0.8893 |
| 0.02          | 18.0  | 3672 | 1.0702          | 0.8940   | 0.8928 |
| 0.02          | 19.0  | 3876 | 0.9675          | 0.8968   | 0.8957 |
| 0.0067        | 20.0  | 4080 | 0.9127          | 0.8968   | 0.8965 |
| 0.0067        | 21.0  | 4284 | 0.9818          | 0.9083   | 0.9075 |
| 0.0067        | 22.0  | 4488 | 0.9895          | 0.8940   | 0.8934 |
| 0.0074        | 23.0  | 4692 | 0.8589          | 0.9054   | 0.9054 |
| 0.0074        | 24.0  | 4896 | 1.0275          | 0.8997   | 0.8992 |
| 0.0139        | 25.0  | 5100 | 0.9546          | 0.9026   | 0.9021 |
| 0.0139        | 26.0  | 5304 | 0.9809          | 0.9083   | 0.9077 |
| 0.0074        | 27.0  | 5508 | 0.9914          | 0.9026   | 0.9020 |
| 0.0074        | 28.0  | 5712 | 0.9072          | 0.9054   | 0.9052 |
| 0.0074        | 29.0  | 5916 | 0.8984          | 0.9083   | 0.9081 |
| 0.0081        | 30.0  | 6120 | 0.9815          | 0.9083   | 0.9074 |
| 0.0081        | 31.0  | 6324 | 0.9143          | 0.8968   | 0.8969 |
| 0.003         | 32.0  | 6528 | 0.9652          | 0.9054   | 0.9044 |
| 0.003         | 33.0  | 6732 | 1.0522          | 0.9054   | 0.9045 |
| 0.003         | 34.0  | 6936 | 1.0332          | 0.9054   | 0.9045 |
| 0.0023        | 35.0  | 7140 | 1.0442          | 0.9054   | 0.9045 |


### Framework versions

- Transformers 4.35.2
- Pytorch 1.13.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.2