---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
model-index:
- name: e5_Mobilite_MultiLabel_12082025
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# e5_Mobilite_MultiLabel_12082025

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: 0.0934
- F1 Weighted: 0.9708

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 0.9493        | 1.0   | 205  | 0.5328          | 0.7827      |
| 0.4552        | 2.0   | 410  | 0.2622          | 0.8897      |
| 0.2754        | 3.0   | 615  | 0.1951          | 0.9142      |
| 0.1966        | 4.0   | 820  | 0.1443          | 0.9431      |
| 0.1493        | 5.0   | 1025 | 0.1290          | 0.9526      |
| 0.1232        | 6.0   | 1230 | 0.1046          | 0.9629      |
| 0.1039        | 7.0   | 1435 | 0.0977          | 0.9667      |
| 0.0875        | 8.0   | 1640 | 0.1080          | 0.9597      |
| 0.0782        | 9.0   | 1845 | 0.0934          | 0.9708      |


### Framework versions

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