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---
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
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