---
license: mit
base_model: camembert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: VogagenRelation
  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. -->

# VogagenRelation

This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4009
- Accuracy: 0.8885

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.21  | 100  | 0.6667          | 0.6006   |
| No log        | 0.42  | 200  | 0.6039          | 0.7137   |
| No log        | 0.62  | 300  | 0.6321          | 0.6677   |
| No log        | 0.83  | 400  | 0.5410          | 0.7715   |
| 0.6555        | 1.04  | 500  | 0.5710          | 0.7317   |
| 0.6555        | 1.25  | 600  | 0.5570          | 0.7621   |
| 0.6555        | 1.46  | 700  | 0.5420          | 0.7769   |
| 0.6555        | 1.66  | 800  | 0.5119          | 0.8011   |
| 0.6555        | 1.87  | 900  | 0.3608          | 0.8674   |
| 0.4846        | 2.08  | 1000 | 0.4312          | 0.8565   |
| 0.4846        | 2.29  | 1100 | 0.5109          | 0.8409   |
| 0.4846        | 2.49  | 1200 | 0.3783          | 0.8768   |
| 0.4846        | 2.7   | 1300 | 0.5244          | 0.8354   |
| 0.4846        | 2.91  | 1400 | 0.3986          | 0.8713   |
| 0.3439        | 3.12  | 1500 | 0.4613          | 0.8736   |
| 0.3439        | 3.33  | 1600 | 0.3658          | 0.8846   |
| 0.3439        | 3.53  | 1700 | 0.3890          | 0.8830   |
| 0.3439        | 3.74  | 1800 | 0.4028          | 0.8877   |
| 0.3439        | 3.95  | 1900 | 0.4009          | 0.8885   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1