---
license: mit
base_model: microsoft/Multilingual-MiniLM-L12-H384
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: intent_trading
  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. -->

# intent_trading

This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1788
- Accuracy: 0.9590

## 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 235  | 1.6327          | 0.6781   |
| No log        | 2.0   | 470  | 1.0073          | 0.8852   |
| 1.7024        | 3.0   | 705  | 0.6035          | 0.9299   |
| 1.7024        | 4.0   | 940  | 0.3965          | 0.9323   |
| 0.5941        | 5.0   | 1175 | 0.2810          | 0.9534   |
| 0.5941        | 6.0   | 1410 | 0.2259          | 0.9531   |
| 0.2567        | 7.0   | 1645 | 0.1949          | 0.9531   |
| 0.2567        | 8.0   | 1880 | 0.1723          | 0.9566   |
| 0.1484        | 9.0   | 2115 | 0.1736          | 0.9558   |
| 0.1484        | 10.0  | 2350 | 0.1545          | 0.9558   |
| 0.1084        | 11.0  | 2585 | 0.1559          | 0.9568   |
| 0.1084        | 12.0  | 2820 | 0.1562          | 0.9536   |
| 0.0824        | 13.0  | 3055 | 0.1486          | 0.9560   |
| 0.0824        | 14.0  | 3290 | 0.1450          | 0.9560   |
| 0.0714        | 15.0  | 3525 | 0.1386          | 0.9568   |
| 0.0714        | 16.0  | 3760 | 0.1412          | 0.9600   |
| 0.0714        | 17.0  | 3995 | 0.1475          | 0.9563   |
| 0.063         | 18.0  | 4230 | 0.1471          | 0.9558   |
| 0.063         | 19.0  | 4465 | 0.1517          | 0.9574   |
| 0.0529        | 20.0  | 4700 | 0.1535          | 0.9550   |
| 0.0529        | 21.0  | 4935 | 0.1494          | 0.9598   |
| 0.0504        | 22.0  | 5170 | 0.1661          | 0.9579   |
| 0.0504        | 23.0  | 5405 | 0.1548          | 0.9592   |
| 0.0453        | 24.0  | 5640 | 0.1584          | 0.9600   |
| 0.0453        | 25.0  | 5875 | 0.1601          | 0.9558   |
| 0.0395        | 26.0  | 6110 | 0.1511          | 0.9598   |
| 0.0395        | 27.0  | 6345 | 0.1655          | 0.9584   |
| 0.0375        | 28.0  | 6580 | 0.1614          | 0.9579   |
| 0.0375        | 29.0  | 6815 | 0.1534          | 0.9595   |
| 0.0332        | 30.0  | 7050 | 0.1757          | 0.9574   |
| 0.0332        | 31.0  | 7285 | 0.1701          | 0.9576   |
| 0.0324        | 32.0  | 7520 | 0.1635          | 0.9587   |
| 0.0324        | 33.0  | 7755 | 0.1721          | 0.9587   |
| 0.0324        | 34.0  | 7990 | 0.1742          | 0.9584   |
| 0.0294        | 35.0  | 8225 | 0.1798          | 0.9582   |
| 0.0294        | 36.0  | 8460 | 0.1812          | 0.9582   |
| 0.029         | 37.0  | 8695 | 0.1759          | 0.9590   |
| 0.029         | 38.0  | 8930 | 0.1777          | 0.9600   |
| 0.028         | 39.0  | 9165 | 0.1782          | 0.9598   |
| 0.028         | 40.0  | 9400 | 0.1788          | 0.9590   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.19.1