---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-base
tags:
- generated_from_trainer
model-index:
- name: e5_General_2026_V2
  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_General_2026_V2

This model is a fine-tuned version of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2693
- F1 Weighted: 0.8980

## 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: 2e-05
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-----------:|
| 0.9259        | 1.0   | 1047  | 0.2613          | 0.8027      |
| 0.4565        | 2.0   | 2094  | 0.2130          | 0.8427      |
| 0.3400        | 3.0   | 3141  | 0.2124          | 0.8579      |
| 0.2721        | 4.0   | 4188  | 0.2109          | 0.8694      |
| 0.2249        | 5.0   | 5235  | 0.2290          | 0.8845      |
| 0.1894        | 6.0   | 6282  | 0.2344          | 0.8825      |
| 0.1568        | 7.0   | 7329  | 0.2507          | 0.8949      |
| 0.1381        | 8.0   | 8376  | 0.2556          | 0.8937      |
| 0.1176        | 9.0   | 9423  | 0.2743          | 0.8974      |
| 0.1108        | 10.0  | 10470 | 0.2693          | 0.8980      |


### Framework versions

- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2