---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: e5_Main_topic_v1
  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_Main_topic_v1

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: 0.0357
- Accuracy: 0.9871
- F1: 0.9872

## 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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3915        | 1.0   | 335  | 0.2420          | 0.9269   | 0.9269 |
| 0.1777        | 2.0   | 670  | 0.0943          | 0.9682   | 0.9683 |
| 0.1244        | 3.0   | 1005 | 0.0757          | 0.9745   | 0.9745 |
| 0.103         | 4.0   | 1340 | 0.0751          | 0.9762   | 0.9763 |
| 0.0881        | 5.0   | 1675 | 0.0860          | 0.9717   | 0.9717 |
| 0.0771        | 6.0   | 2010 | 0.0454          | 0.9852   | 0.9852 |
| 0.0663        | 7.0   | 2345 | 0.0450          | 0.9851   | 0.9852 |
| 0.0634        | 8.0   | 2680 | 0.0454          | 0.9839   | 0.9839 |
| 0.0614        | 9.0   | 3015 | 0.0357          | 0.9871   | 0.9872 |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1