---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: e5_Eau_v4
  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_v4

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: 0.3106
- Accuracy: 0.9147
- F1: 0.9144

## 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: 8
- total_train_batch_size: 64
- 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
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.6724        | 1.0   | 74   | 0.5272          | 0.8167   | 0.8200 |
| 0.6907        | 2.0   | 148  | 0.2947          | 0.8742   | 0.8777 |
| 0.2007        | 3.0   | 222  | 0.2195          | 0.9231   | 0.9237 |
| 0.1678        | 4.0   | 296  | 0.2200          | 0.9223   | 0.9238 |
| 0.0963        | 5.0   | 370  | 0.2838          | 0.9164   | 0.9185 |
| 0.0783        | 6.0   | 444  | 0.2990          | 0.9172   | 0.9192 |
| 0.0722        | 7.0   | 518  | 0.3106          | 0.9147   | 0.9144 |


### Framework versions

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