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---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: distilcamembert-base-cae
  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. -->

# distilcamembert-base-cae

This model is a fine-tuned version of [cmarkea/distilcamembert-base](https://huggingface.co/cmarkea/distilcamembert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6618
- Precision: 0.8838
- Recall: 0.8835
- F1: 0.8833

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 1.4308        | 1.0   | 292  | 0.5898          | 0.8153    | 0.8286 | 0.8134 |
| 0.4963        | 2.0   | 584  | 0.4794          | 0.8339    | 0.8518 | 0.8416 |
| 0.2939        | 3.0   | 876  | 0.5137          | 0.8718    | 0.8629 | 0.8574 |
| 0.1786        | 4.0   | 1168 | 0.5439          | 0.8777    | 0.8698 | 0.8659 |
| 0.1277        | 5.0   | 1460 | 0.5820          | 0.8701    | 0.8715 | 0.8701 |
| 0.0817        | 6.0   | 1752 | 0.5889          | 0.8803    | 0.8800 | 0.8800 |
| 0.0659        | 7.0   | 2044 | 0.6385          | 0.8734    | 0.8757 | 0.8741 |
| 0.0497        | 8.0   | 2336 | 0.6521          | 0.8806    | 0.8783 | 0.8789 |
| 0.0432        | 9.0   | 2628 | 0.6618          | 0.8838    | 0.8835 | 0.8833 |
| 0.039         | 10.0  | 2920 | 0.6583          | 0.8810    | 0.8809 | 0.8807 |


### Framework versions

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