---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
model-index:
- name: e5_Eau_MultiLabel_Augmented_v1
  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_Augmented_v1

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: 0.1429
- F1 Weighted: 0.9465

## 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 0.8715        | 1.0   | 296  | 0.4957          | 0.7559      |
| 0.4536        | 2.0   | 592  | 0.3266          | 0.8547      |
| 0.3144        | 3.0   | 888  | 0.2843          | 0.8657      |
| 0.2448        | 4.0   | 1184 | 0.2369          | 0.8989      |
| 0.1999        | 5.0   | 1480 | 0.1980          | 0.9154      |
| 0.1683        | 6.0   | 1776 | 0.1881          | 0.9245      |
| 0.1452        | 7.0   | 2072 | 0.1763          | 0.9293      |
| 0.1261        | 8.0   | 2368 | 0.1671          | 0.9326      |
| 0.1098        | 9.0   | 2664 | 0.1557          | 0.9432      |
| 0.0985        | 10.0  | 2960 | 0.1541          | 0.9430      |
| 0.0899        | 11.0  | 3256 | 0.1508          | 0.9440      |
| 0.083         | 12.0  | 3552 | 0.1429          | 0.9465      |


### Framework versions

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