---
license: mit
base_model: microsoft/Multilingual-MiniLM-L12-H384
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Multilingual-MiniLM-L12-H384-finetunned-elementos-contractuales
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Multilingual-MiniLM-L12-H384-finetunned-elementos-contractuales

This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3775
- Accuracy: 0.9191
- F1: 0.8991

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 23   | 0.9210          | 0.7353   | 0.6231 |
| No log        | 2.0   | 46   | 0.7792          | 0.7353   | 0.6231 |
| No log        | 3.0   | 69   | 0.7253          | 0.7059   | 0.6319 |
| No log        | 4.0   | 92   | 0.5066          | 0.9162   | 0.8966 |
| No log        | 5.0   | 115  | 0.4528          | 0.9191   | 0.8993 |
| No log        | 6.0   | 138  | 0.4201          | 0.9221   | 0.9021 |
| No log        | 7.0   | 161  | 0.4033          | 0.9206   | 0.9013 |
| No log        | 8.0   | 184  | 0.3979          | 0.9132   | 0.8928 |
| No log        | 9.0   | 207  | 0.3777          | 0.9221   | 0.9027 |
| No log        | 10.0  | 230  | 0.3775          | 0.9191   | 0.8991 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1