---
license: cc-by-4.0
base_model: qanastek/XLMRoberta-Alexa-Intents-Classification
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: intent_classification_model
  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_classification_model

This model is a fine-tuned version of [qanastek/XLMRoberta-Alexa-Intents-Classification](https://huggingface.co/qanastek/XLMRoberta-Alexa-Intents-Classification) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3184
- Accuracy: 0.9409

## 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: 128
- eval_batch_size: 128
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1893        | 4.0   | 712  | 1.0851          | 0.6870   |
| 0.6443        | 8.0   | 1424 | 0.6027          | 0.8489   |
| 0.294         | 12.0  | 2136 | 0.3864          | 0.9179   |
| 0.2081        | 16.0  | 2848 | 0.3309          | 0.9369   |
| 0.1274        | 20.0  | 3560 | 0.3184          | 0.9409   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1