|
--- |
|
language: |
|
- de |
|
- fr |
|
- it |
|
- pt |
|
- es |
|
- pl |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
- nlu |
|
- text-classification |
|
- intent-classification |
|
datasets: |
|
- AmazonScience/massive |
|
metrics: |
|
- accuracy |
|
- f1 |
|
base_model: microsoft/Multilingual-MiniLM-L12-H384 |
|
model-index: |
|
- name: multilingual_minilm-amazon_massive-intent_eu_noen |
|
results: |
|
- task: |
|
type: intent-classification |
|
name: intent-classification |
|
dataset: |
|
name: MASSIVE |
|
type: AmazonScience/massive |
|
split: test |
|
metrics: |
|
- type: f1 |
|
value: 0.8551 |
|
name: F1 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# multilingual_minilm-amazon_massive-intent_eu_noen |
|
|
|
This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the [MASSIVE1.1](https://huggingface.co/datasets/AmazonScience/massive) dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7794 |
|
- Accuracy: 0.8551 |
|
- F1: 0.8551 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| |
|
| 1.7624 | 1.0 | 4318 | 1.5462 | 0.6331 | 0.6331 | |
|
| 0.9535 | 2.0 | 8636 | 0.9628 | 0.7698 | 0.7698 | |
|
| 0.6849 | 3.0 | 12954 | 0.8034 | 0.8097 | 0.8097 | |
|
| 0.5163 | 4.0 | 17272 | 0.7444 | 0.8290 | 0.8290 | |
|
| 0.3973 | 5.0 | 21590 | 0.7346 | 0.8383 | 0.8383 | |
|
| 0.331 | 6.0 | 25908 | 0.7369 | 0.8453 | 0.8453 | |
|
| 0.2876 | 7.0 | 30226 | 0.7325 | 0.8510 | 0.8510 | |
|
| 0.2319 | 8.0 | 34544 | 0.7726 | 0.8496 | 0.8496 | |
|
| 0.2098 | 9.0 | 38862 | 0.7803 | 0.8543 | 0.8543 | |
|
| 0.1863 | 10.0 | 43180 | 0.7794 | 0.8551 | 0.8551 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.13.1+cu116 |
|
- Datasets 2.8.0 |
|
- Tokenizers 0.13.2 |
