---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
model-index:
- name: e5_Dechets_MultiLabel_08092025
  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. -->

# e5_Dechets_MultiLabel_08092025

This model is a fine-tuned version of [intfloat/multilingual-e5-large-instruct](https://huggingface.co/intfloat/multilingual-e5-large-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1811
- F1 Weighted: 0.9499

## 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-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 0.8583        | 1.0   | 199  | 0.5295          | 0.7662      |
| 0.4704        | 2.0   | 398  | 0.3538          | 0.8660      |
| 0.3289        | 3.0   | 597  | 0.2997          | 0.8879      |
| 0.2543        | 4.0   | 796  | 0.2687          | 0.9014      |
| 0.2075        | 5.0   | 995  | 0.2480          | 0.9182      |
| 0.1755        | 6.0   | 1194 | 0.2326          | 0.9248      |
| 0.1486        | 7.0   | 1393 | 0.2227          | 0.9290      |
| 0.1285        | 8.0   | 1592 | 0.2051          | 0.9391      |
| 0.1114        | 9.0   | 1791 | 0.1907          | 0.9434      |
| 0.1007        | 10.0  | 1990 | 0.1889          | 0.9459      |
| 0.0896        | 11.0  | 2189 | 0.1811          | 0.9499      |


### Framework versions

- Transformers 4.56.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0