---
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: 0.1741
- Accuracy: 0.9548

## 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   | 227  | 1.5904          | 0.7689   |
| No log        | 2.0   | 454  | 1.0086          | 0.8670   |
| 1.6528        | 3.0   | 681  | 0.6706          | 0.9055   |
| 1.6528        | 4.0   | 908  | 0.4376          | 0.9518   |
| 0.6124        | 5.0   | 1135 | 0.2966          | 0.9551   |
| 0.6124        | 6.0   | 1362 | 0.2373          | 0.9504   |
| 0.2536        | 7.0   | 1589 | 0.1967          | 0.9537   |
| 0.2536        | 8.0   | 1816 | 0.1666          | 0.9565   |
| 0.1476        | 9.0   | 2043 | 0.1642          | 0.9543   |
| 0.1476        | 10.0  | 2270 | 0.1570          | 0.9551   |
| 0.1476        | 11.0  | 2497 | 0.1500          | 0.9543   |
| 0.1067        | 12.0  | 2724 | 0.1469          | 0.9548   |
| 0.1067        | 13.0  | 2951 | 0.1458          | 0.9557   |
| 0.0817        | 14.0  | 3178 | 0.1409          | 0.9540   |
| 0.0817        | 15.0  | 3405 | 0.1426          | 0.9595   |
| 0.0709        | 16.0  | 3632 | 0.1418          | 0.9540   |
| 0.0709        | 17.0  | 3859 | 0.1416          | 0.9557   |
| 0.0631        | 18.0  | 4086 | 0.1373          | 0.9581   |
| 0.0631        | 19.0  | 4313 | 0.1458          | 0.9559   |
| 0.0557        | 20.0  | 4540 | 0.1391          | 0.9559   |
| 0.0557        | 21.0  | 4767 | 0.1526          | 0.9518   |
| 0.0557        | 22.0  | 4994 | 0.1511          | 0.9529   |
| 0.0495        | 23.0  | 5221 | 0.1578          | 0.9526   |
| 0.0495        | 24.0  | 5448 | 0.1360          | 0.9568   |
| 0.0443        | 25.0  | 5675 | 0.1451          | 0.9565   |
| 0.0443        | 26.0  | 5902 | 0.1477          | 0.9562   |
| 0.0419        | 27.0  | 6129 | 0.1624          | 0.9540   |
| 0.0419        | 28.0  | 6356 | 0.1659          | 0.9537   |
| 0.0371        | 29.0  | 6583 | 0.1607          | 0.9548   |
| 0.0371        | 30.0  | 6810 | 0.1638          | 0.9543   |
| 0.035         | 31.0  | 7037 | 0.1655          | 0.9529   |
| 0.035         | 32.0  | 7264 | 0.1662          | 0.9562   |
| 0.035         | 33.0  | 7491 | 0.1702          | 0.9532   |
| 0.033         | 34.0  | 7718 | 0.1662          | 0.9562   |
| 0.033         | 35.0  | 7945 | 0.1667          | 0.9532   |
| 0.0309        | 36.0  | 8172 | 0.1794          | 0.9554   |
| 0.0309        | 37.0  | 8399 | 0.1756          | 0.9546   |
| 0.0292        | 38.0  | 8626 | 0.1722          | 0.9559   |
| 0.0292        | 39.0  | 8853 | 0.1706          | 0.9559   |
| 0.0281        | 40.0  | 9080 | 0.1741          | 0.9548   |


### Framework versions

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