---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
model-index:
- name: e5_Eau_MultiLabel_Simple_v2
  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_Simple_v2

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: 0.2521
- F1 Weighted: 0.9002

## 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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 1.0079        | 1.0   | 148  | 0.7728          | 0.6280      |
| 0.7019        | 2.0   | 296  | 0.4871          | 0.7514      |
| 0.4819        | 3.0   | 444  | 0.3662          | 0.8241      |
| 0.3789        | 4.0   | 592  | 0.3188          | 0.8487      |
| 0.3105        | 5.0   | 740  | 0.2885          | 0.8662      |
| 0.2679        | 6.0   | 888  | 0.2747          | 0.8797      |
| 0.23          | 7.0   | 1036 | 0.2605          | 0.8822      |
| 0.2067        | 8.0   | 1184 | 0.2539          | 0.8880      |
| 0.1868        | 9.0   | 1332 | 0.2489          | 0.8940      |
| 0.1676        | 10.0  | 1480 | 0.2507          | 0.8980      |
| 0.1545        | 11.0  | 1628 | 0.2518          | 0.9008      |
| 0.1429        | 12.0  | 1776 | 0.2521          | 0.9002      |


### Framework versions

- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2