---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: camembert-secabilite-regressor
  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. -->

# camembert-secabilite-regressor

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0136
- Model Preparation Time: 0.0011
- Mse: 0.0137
- Mae: 0.0557

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Mse    | Mae    |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:------:|
| 0.0102        | 1.0   | 108  | 0.0136          | 0.0011                 | 0.0137 | 0.0624 |
| 0.0095        | 2.0   | 216  | 0.0144          | 0.0011                 | 0.0144 | 0.0607 |
| 0.0089        | 3.0   | 324  | 0.0141          | 0.0011                 | 0.0141 | 0.0590 |
| 0.0089        | 4.0   | 432  | 0.0139          | 0.0011                 | 0.0140 | 0.0576 |
| 0.009         | 5.0   | 540  | 0.0138          | 0.0011                 | 0.0139 | 0.0568 |
| 0.0091        | 6.0   | 648  | 0.0136          | 0.0011                 | 0.0137 | 0.0561 |
| 0.0085        | 7.0   | 756  | 0.0136          | 0.0011                 | 0.0137 | 0.0557 |
| 0.0084        | 8.0   | 864  | 0.0136          | 0.0011                 | 0.0137 | 0.0557 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0
- Datasets 3.5.0
- Tokenizers 0.21.1