---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
model-index:
- name: e5_Eau_Multilabel_Topic_Sentiment
  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_Topic_Sentiment

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: 0.1566
- F1 Topic: 0.9104
- F1 Sentiment: 0.8933
- F1 Macro Avg: 0.9019

## 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: 1e-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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Topic | F1 Sentiment | F1 Macro Avg |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------------:|:------------:|
| 0.5731        | 1.0   | 148  | 0.4031          | 0.4584   | 0.6075       | 0.5330       |
| 0.2812        | 2.0   | 296  | 0.1726          | 0.7873   | 0.8019       | 0.7946       |
| 0.1396        | 3.0   | 444  | 0.1214          | 0.8694   | 0.8576       | 0.8635       |
| 0.0982        | 4.0   | 592  | 0.1244          | 0.8886   | 0.8643       | 0.8765       |
| 0.0732        | 5.0   | 740  | 0.1311          | 0.9118   | 0.8850       | 0.8984       |
| 0.0508        | 6.0   | 888  | 0.1566          | 0.9104   | 0.8933       | 0.9019       |


### Framework versions

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