---
library_name: transformers
license: apache-2.0
base_model: Alibaba-NLP/gte-multilingual-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: gte-multilingual-base-edu-scorer-lr3e4-bs32
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# gte-multilingual-base-edu-scorer-lr3e4-bs32

This model is a fine-tuned version of [Alibaba-NLP/gte-multilingual-base](https://huggingface.co/Alibaba-NLP/gte-multilingual-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4840
- Precision: 0.0303
- Recall: 0.1667
- F1 Macro: 0.0513
- Accuracy: 0.1818

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1 Macro | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
| No log        | 0      | 0    | 3.8217          | 0.0587    | 0.1667 | 0.0869   | 0.3524   |
| 1.6594        | 0.3368 | 1000 | 1.5917          | 0.0516    | 0.1667 | 0.0788   | 0.3094   |
| 1.5964        | 0.6736 | 2000 | 1.5910          | 0.0516    | 0.1667 | 0.0788   | 0.3094   |
| 1.6156        | 1.0104 | 3000 | 1.5900          | 0.0516    | 0.1667 | 0.0788   | 0.3094   |
| 1.586         | 1.3473 | 4000 | 1.5905          | 0.0516    | 0.1667 | 0.0788   | 0.3094   |
| 1.5427        | 1.6841 | 5000 | 1.5903          | 0.0516    | 0.1667 | 0.0788   | 0.3094   |


### Framework versions

- Transformers 4.53.2
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2