README.md

---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-arabic-finetuned-on-halabi_daataset_with-diacritics-2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper-small-arabic-finetuned-on-halabi_daataset_with-diacritics-2

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7378
- Wer: 0.7221

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 1000

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.0504        | 3.5133  | 200  | 0.7435          | 0.7221 |
| 0.0138        | 7.0177  | 400  | 0.9074          | 0.7135 |
| 0.0049        | 10.5310 | 600  | 1.1826          | 0.7156 |
| 0.0013        | 14.0354 | 800  | 1.1966          | 0.7156 |
| 0.0008        | 17.5487 | 1000 | 1.1947          | 0.7163 |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3