LABEL_0 LABEL_1 LABEL_2 LABEL_3 LABEL_4 LABEL_5 LABEL_6 LABEL_7 LABEL_8
---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: test_trainer
  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. -->

# test_trainer

This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5153
- Precision: 0.8965
- Recall: 0.8946
- F1: 0.8950

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 1.6953        | 1.0   | 292  | 0.8195          | 0.8238    | 0.8003 | 0.7599 |
| 0.6393        | 2.0   | 584  | 0.5050          | 0.8479    | 0.8663 | 0.8558 |
| 0.4071        | 3.0   | 876  | 0.4896          | 0.8525    | 0.8680 | 0.8582 |
| 0.2786        | 4.0   | 1168 | 0.4720          | 0.8842    | 0.8835 | 0.8787 |
| 0.1997        | 5.0   | 1460 | 0.5115          | 0.8832    | 0.8843 | 0.8828 |
| 0.1464        | 6.0   | 1752 | 0.5247          | 0.8863    | 0.8843 | 0.8842 |
| 0.1114        | 7.0   | 2044 | 0.5193          | 0.8946    | 0.8929 | 0.8933 |
| 0.0836        | 8.0   | 2336 | 0.5153          | 0.8965    | 0.8946 | 0.8950 |
| 0.0727        | 9.0   | 2628 | 0.5403          | 0.8896    | 0.8895 | 0.8891 |
| 0.0597        | 10.0  | 2920 | 0.5471          | 0.8889    | 0.8886 | 0.8883 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
