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---
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
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