---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
model-index:
- name: e5_RSE_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_RSE_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: 0.2425
- F1 Weighted: 0.8843

## 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-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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 1.0829        | 1.0   | 178  | 0.8684          | 0.5980      |
| 0.8123        | 2.0   | 356  | 0.5814          | 0.6966      |
| 0.6025        | 3.0   | 534  | 0.4584          | 0.7583      |
| 0.4907        | 4.0   | 712  | 0.3871          | 0.7954      |
| 0.422         | 5.0   | 890  | 0.3562          | 0.8068      |
| 0.3762        | 6.0   | 1068 | 0.3218          | 0.8299      |
| 0.3347        | 7.0   | 1246 | 0.3066          | 0.8399      |
| 0.3032        | 8.0   | 1424 | 0.2843          | 0.8505      |
| 0.2782        | 9.0   | 1602 | 0.2726          | 0.8592      |
| 0.2527        | 10.0  | 1780 | 0.2639          | 0.8653      |
| 0.2352        | 11.0  | 1958 | 0.2632          | 0.8648      |
| 0.2211        | 12.0  | 2136 | 0.2549          | 0.8717      |
| 0.2076        | 13.0  | 2314 | 0.2557          | 0.8746      |
| 0.1963        | 14.0  | 2492 | 0.2467          | 0.8816      |
| 0.1865        | 15.0  | 2670 | 0.2471          | 0.8808      |
| 0.1808        | 16.0  | 2848 | 0.2471          | 0.8829      |
| 0.1755        | 17.0  | 3026 | 0.2391          | 0.8873      |
| 0.1723        | 18.0  | 3204 | 0.2404          | 0.8853      |
| 0.1665        | 19.0  | 3382 | 0.2434          | 0.8848      |
| 0.1643        | 20.0  | 3560 | 0.2425          | 0.8843      |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0