---
license: mit
base_model: camembert-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: result
  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. -->

# result

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: 0.0181
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9960

## 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: 0.00025
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log        | 1.0   | 25   | 0.0900          | 0.0       | 0.0    | 0.0 | 0.9818   |
| No log        | 2.0   | 50   | 0.0557          | 0.0       | 0.0    | 0.0 | 0.9822   |
| No log        | 3.0   | 75   | 0.0546          | 0.0       | 0.0    | 0.0 | 0.9889   |
| No log        | 4.0   | 100  | 0.0287          | 0.0       | 0.0    | 0.0 | 0.9945   |
| No log        | 5.0   | 125  | 0.0240          | 0.0       | 0.0    | 0.0 | 0.9941   |
| No log        | 6.0   | 150  | 0.0179          | 0.0       | 0.0    | 0.0 | 0.9956   |
| No log        | 7.0   | 175  | 0.0163          | 0.0       | 0.0    | 0.0 | 0.9964   |
| No log        | 8.0   | 200  | 0.0189          | 0.0       | 0.0    | 0.0 | 0.9952   |
| No log        | 9.0   | 225  | 0.0169          | 0.0       | 0.0    | 0.0 | 0.9960   |
| No log        | 10.0  | 250  | 0.0145          | 0.0       | 0.0    | 0.0 | 0.9968   |
| No log        | 11.0  | 275  | 0.0164          | 0.0       | 0.0    | 0.0 | 0.9964   |
| No log        | 12.0  | 300  | 0.0153          | 0.0       | 0.0    | 0.0 | 0.9964   |
| No log        | 13.0  | 325  | 0.0153          | 0.0       | 0.0    | 0.0 | 0.9964   |
| No log        | 14.0  | 350  | 0.0161          | 0.0       | 0.0    | 0.0 | 0.9964   |
| No log        | 15.0  | 375  | 0.0164          | 0.0       | 0.0    | 0.0 | 0.9964   |
| No log        | 16.0  | 400  | 0.0166          | 0.0       | 0.0    | 0.0 | 0.9964   |
| No log        | 17.0  | 425  | 0.0161          | 0.0       | 0.0    | 0.0 | 0.9964   |
| No log        | 18.0  | 450  | 0.0166          | 0.0       | 0.0    | 0.0 | 0.9956   |
| No log        | 19.0  | 475  | 0.0182          | 0.0       | 0.0    | 0.0 | 0.9960   |
| 0.0262        | 20.0  | 500  | 0.0181          | 0.0       | 0.0    | 0.0 | 0.9960   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0