---
tags:
- generated_from_trainer
datasets:
- custom
model-index:
- name: xlm_r-joint_nlu-custom_ds
  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. -->

# xlm_r-joint_nlu-custom_ds

This model was trained from scratch on the custom dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0312
- Intent Accuracy: 1.0
- Intent F1 Macro: 1.0
- Slot F1: 0.9506
- Semantic Accuracy: 0.9474

Evaluation on the test set:
- Intent Accuracy: 1.0
- Slot F1: 0.9506294471811714
- Semantic Accuracy: 0.9473684210526315

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Intent Accuracy | Intent F1 Macro | Slot F1 | Semantic Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:---------------:|:-------:|:-----------------:|
| No log        | 1.0   | 47   | 2.1385          | 0.6809          | 0.4650          | 0.1429  | 0.1809            |
| No log        | 2.0   | 94   | 1.0050          | 0.9043          | 0.8890          | 0.2806  | 0.2128            |
| No log        | 3.0   | 141  | 0.4169          | 0.9787          | 0.9582          | 0.3632  | 0.2660            |
| No log        | 4.0   | 188  | 0.2661          | 0.9894          | 0.9798          | 0.6908  | 0.5745            |
| No log        | 5.0   | 235  | 0.2036          | 0.9894          | 0.9798          | 0.7454  | 0.5532            |
| No log        | 6.0   | 282  | 0.1547          | 0.9894          | 0.9881          | 0.7699  | 0.6489            |
| No log        | 7.0   | 329  | 0.1094          | 1.0             | 1.0             | 0.8216  | 0.6596            |
| No log        | 8.0   | 376  | 0.1061          | 1.0             | 1.0             | 0.9080  | 0.7128            |
| No log        | 9.0   | 423  | 0.0639          | 1.0             | 1.0             | 0.9575  | 0.8511            |
| No log        | 10.0  | 470  | 0.0571          | 1.0             | 1.0             | 0.9597  | 0.8511            |
| 0.7099        | 11.0  | 517  | 0.0527          | 1.0             | 1.0             | 0.9763  | 0.8723            |
| 0.7099        | 12.0  | 564  | 0.0408          | 1.0             | 1.0             | 0.9708  | 0.8723            |
| 0.7099        | 13.0  | 611  | 0.0415          | 1.0             | 1.0             | 0.9899  | 0.9043            |
| 0.7099        | 14.0  | 658  | 0.0347          | 1.0             | 1.0             | 0.9661  | 0.9149            |
| 0.7099        | 15.0  | 705  | 0.0388          | 1.0             | 1.0             | 0.9899  | 0.9149            |
| 0.7099        | 16.0  | 752  | 0.0333          | 1.0             | 1.0             | 0.9983  | 0.9255            |
| 0.7099        | 17.0  | 799  | 0.0533          | 1.0             | 1.0             | 0.9899  | 0.8936            |
| 0.7099        | 18.0  | 846  | 0.0404          | 1.0             | 1.0             | 0.9899  | 0.9043            |
| 0.7099        | 19.0  | 893  | 0.0408          | 1.0             | 1.0             | 0.9805  | 0.9043            |
| 0.7099        | 20.0  | 940  | 0.0387          | 1.0             | 1.0             | 0.9899  | 0.9255            |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0