---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
model-index:
- name: e5_Eau_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_Eau_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: 0.1092
- F1 Weighted: 0.9588

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 0.8445        | 1.0   | 320  | 0.4706          | 0.7681      |
| 0.4237        | 2.0   | 640  | 0.2907          | 0.8595      |
| 0.2906        | 3.0   | 960  | 0.2338          | 0.8938      |
| 0.2215        | 4.0   | 1280 | 0.1836          | 0.9217      |
| 0.179         | 5.0   | 1600 | 0.1627          | 0.9299      |
| 0.1513        | 6.0   | 1920 | 0.1523          | 0.9376      |
| 0.1266        | 7.0   | 2240 | 0.1457          | 0.9376      |
| 0.1101        | 8.0   | 2560 | 0.1351          | 0.9428      |
| 0.0965        | 9.0   | 2880 | 0.1199          | 0.9509      |
| 0.0873        | 10.0  | 3200 | 0.1175          | 0.9554      |
| 0.0767        | 11.0  | 3520 | 0.1180          | 0.9564      |
| 0.0707        | 12.0  | 3840 | 0.1092          | 0.9588      |


### Framework versions

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