---
library_name: transformers
license: mit
base_model: almanach/camembert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bert-small-paragraph-classifier
  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. -->

# bert-small-paragraph-classifier

This model is a fine-tuned version of [almanach/camembert-base](https://huggingface.co/almanach/camembert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1045
- Accuracy: 0.9983
- Precision: 0.9983
- Recall: 0.9983
- F1: 0.9983

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 338  | 0.1045          | 0.9983   | 0.9983    | 0.9983 | 0.9983 |
| 0.4417        | 2.0   | 676  | 0.0408          | 0.9983   | 0.9983    | 0.9983 | 0.9983 |
| 0.0461        | 3.0   | 1014 | 0.0291          | 0.9983   | 0.9983    | 0.9983 | 0.9983 |


### Framework versions

- Transformers 4.53.1
- Pytorch 2.7.1
- Datasets 3.6.0
- Tokenizers 0.21.2