---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: distilcamembert-cae-no-territory
  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-cae-no-territory

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: 0.6885
- Precision: 0.7873
- Recall: 0.7848
- F1: 0.7855

## 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 1.1796        | 1.0   | 40   | 0.9743          | 0.5640    | 0.4937 | 0.3731 |
| 0.8788        | 2.0   | 80   | 0.8037          | 0.7438    | 0.6709 | 0.6472 |
| 0.4982        | 3.0   | 120  | 0.7692          | 0.8264    | 0.7089 | 0.7558 |
| 0.2865        | 4.0   | 160  | 0.7676          | 0.7498    | 0.7215 | 0.7192 |
| 0.1502        | 5.0   | 200  | 0.6885          | 0.7873    | 0.7848 | 0.7855 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2