|
--- |
|
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 |
|
|
