---
license: mit
base_model: camembert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
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: 0.6952
- Accuracy: 0.5
- Precision: 0.5
- Recall: 1.0
- F1: 0.6667

## 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 | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 0.21  | 100  | 0.6928          | 0.5      | 0.5       | 1.0    | 0.6667 |
| No log        | 0.42  | 200  | 0.7024          | 0.5      | 0.0       | 0.0    | 0.0    |
| No log        | 0.62  | 300  | 0.7194          | 0.5      | 0.0       | 0.0    | 0.0    |
| No log        | 0.83  | 400  | 0.6944          | 0.4992   | 0.0       | 0.0    | 0.0    |
| 0.6974        | 1.04  | 500  | 0.6973          | 0.5      | 0.5       | 1.0    | 0.6667 |
| 0.6974        | 1.25  | 600  | 0.7078          | 0.5      | 0.5       | 1.0    | 0.6667 |
| 0.6974        | 1.46  | 700  | 0.6945          | 0.5      | 0.5       | 1.0    | 0.6667 |
| 0.6974        | 1.66  | 800  | 0.6942          | 0.5      | 0.5       | 1.0    | 0.6667 |
| 0.6974        | 1.87  | 900  | 0.6945          | 0.5      | 0.5       | 1.0    | 0.6667 |
| 0.6962        | 2.08  | 1000 | 0.6932          | 0.4992   | 0.4       | 0.0031 | 0.0062 |
| 0.6962        | 2.29  | 1100 | 0.6952          | 0.5      | 0.5       | 1.0    | 0.6667 |


### Framework versions

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