---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
model-index:
- name: e5_Mobilite_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_Mobilite_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: 0.1036
- F1 Weighted: 0.9654

## 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 0.9387        | 1.0   | 215  | 0.5420          | 0.7745      |
| 0.462         | 2.0   | 430  | 0.2956          | 0.8519      |
| 0.2859        | 3.0   | 645  | 0.2135          | 0.8941      |
| 0.208         | 4.0   | 860  | 0.1591          | 0.9349      |
| 0.1652        | 5.0   | 1075 | 0.1513          | 0.9327      |
| 0.1366        | 6.0   | 1290 | 0.1273          | 0.9509      |
| 0.1177        | 7.0   | 1505 | 0.1197          | 0.9535      |
| 0.1047        | 8.0   | 1720 | 0.1088          | 0.9616      |
| 0.0977        | 9.0   | 1935 | 0.1076          | 0.9616      |
| 0.0918        | 10.0  | 2150 | 0.1036          | 0.9654      |


### Framework versions

- Transformers 4.56.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0