---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: arabic-alphabet-speech-classification
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/kichsan92/huggingface/runs/ww9x1oum)
# arabic-alphabet-speech-classification

This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0156
- Accuracy: 0.9980

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0669        | 1.0   | 2220  | 0.9510          | 0.7601   |
| 0.2059        | 2.0   | 4440  | 0.0944          | 0.9718   |
| 0.0457        | 3.0   | 6660  | 0.0452          | 0.9863   |
| 0.0067        | 4.0   | 8880  | 0.0475          | 0.9903   |
| 0.0001        | 5.0   | 11100 | 0.0316          | 0.9923   |
| 0.0121        | 6.0   | 13320 | 0.0377          | 0.9926   |
| 0.0001        | 7.0   | 15540 | 0.0214          | 0.9950   |
| 0.0           | 8.0   | 17760 | 0.0226          | 0.9968   |
| 0.0           | 9.0   | 19980 | 0.0156          | 0.9980   |
| 0.0           | 10.0  | 22200 | 0.0117          | 0.9977   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1