---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
model-index:
- name: e5_RSE_MultiLabel_06082025
  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_06082025

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: 0.1417
- F1 Weighted: 0.9479

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 0.9065        | 1.0   | 276  | 0.5238          | 0.7205      |
| 0.4792        | 2.0   | 552  | 0.3395          | 0.8138      |
| 0.3315        | 3.0   | 828  | 0.2634          | 0.8660      |
| 0.2536        | 4.0   | 1104 | 0.2347          | 0.8898      |
| 0.2039        | 5.0   | 1380 | 0.2079          | 0.9054      |
| 0.1671        | 6.0   | 1656 | 0.1819          | 0.9228      |
| 0.1403        | 7.0   | 1932 | 0.1779          | 0.9260      |
| 0.121         | 8.0   | 2208 | 0.1647          | 0.9340      |
| 0.1069        | 9.0   | 2484 | 0.1544          | 0.9404      |
| 0.0917        | 10.0  | 2760 | 0.1495          | 0.9456      |
| 0.0828        | 11.0  | 3036 | 0.1470          | 0.9461      |
| 0.0753        | 12.0  | 3312 | 0.1420          | 0.9481      |
| 0.0696        | 13.0  | 3588 | 0.1417          | 0.9479      |


### Framework versions

- Transformers 4.55.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4