---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
model-index:
- name: e5_EC_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_EC_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: 0.1035
- F1 Weighted: 0.9609

## 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 0.822         | 1.0   | 359  | 0.4715          | 0.7472      |
| 0.4137        | 2.0   | 718  | 0.2841          | 0.8514      |
| 0.2836        | 3.0   | 1077 | 0.2275          | 0.8854      |
| 0.214         | 4.0   | 1436 | 0.1941          | 0.9035      |
| 0.1697        | 5.0   | 1795 | 0.1617          | 0.9244      |
| 0.1362        | 6.0   | 2154 | 0.1396          | 0.9361      |
| 0.1141        | 7.0   | 2513 | 0.1285          | 0.9408      |
| 0.0926        | 8.0   | 2872 | 0.1243          | 0.9476      |
| 0.0788        | 9.0   | 3231 | 0.1081          | 0.9542      |
| 0.0685        | 10.0  | 3590 | 0.1111          | 0.9574      |
| 0.0571        | 11.0  | 3949 | 0.1069          | 0.9613      |
| 0.0529        | 12.0  | 4308 | 0.1035          | 0.9609      |


### Framework versions

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