---
library_name: transformers
license: apache-2.0
base_model: arbml/whisper-small-ar
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: whisper-small-ar-eos-v6-mulaw
  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. -->

# whisper-small-ar-eos-v6-mulaw

This model is a fine-tuned version of [arbml/whisper-small-ar](https://huggingface.co/arbml/whisper-small-ar) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7786
- Accuracy: 0.7073

## 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: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.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: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8494        | 1.0   | 557   | 0.8372          | 0.5987   |
| 0.7418        | 2.0   | 1114  | 0.7249          | 0.7012   |
| 0.7201        | 3.0   | 1671  | 0.7034          | 0.7144   |
| 0.7032        | 4.0   | 2228  | 0.6996          | 0.7123   |
| 0.7016        | 5.0   | 2785  | 0.6956          | 0.7169   |
| 0.64          | 6.0   | 3342  | 0.7002          | 0.7184   |
| 0.6507        | 7.0   | 3899  | 0.6937          | 0.7245   |
| 0.6972        | 8.0   | 4456  | 0.6966          | 0.7235   |
| 0.6435        | 9.0   | 5013  | 0.6954          | 0.7260   |
| 0.6437        | 10.0  | 5570  | 0.6969          | 0.7194   |
| 0.675         | 11.0  | 6127  | 0.7022          | 0.7225   |
| 0.6486        | 12.0  | 6684  | 0.7024          | 0.7220   |
| 0.5699        | 13.0  | 7241  | 0.7103          | 0.7199   |
| 0.6024        | 14.0  | 7798  | 0.7070          | 0.7220   |
| 0.6019        | 15.0  | 8355  | 0.7145          | 0.7220   |
| 0.6209        | 16.0  | 8912  | 0.7201          | 0.7230   |
| 0.5811        | 17.0  | 9469  | 0.7241          | 0.7210   |
| 0.5941        | 18.0  | 10026 | 0.7281          | 0.7199   |
| 0.5847        | 19.0  | 10583 | 0.7371          | 0.7210   |
| 0.5309        | 20.0  | 11140 | 0.7435          | 0.7098   |
| 0.5697        | 21.0  | 11697 | 0.7490          | 0.7128   |
| 0.5536        | 22.0  | 12254 | 0.7534          | 0.7103   |
| 0.5517        | 23.0  | 12811 | 0.7636          | 0.7118   |
| 0.5907        | 24.0  | 13368 | 0.7624          | 0.7123   |
| 0.5081        | 25.0  | 13925 | 0.7674          | 0.7103   |
| 0.5305        | 26.0  | 14482 | 0.7706          | 0.7103   |
| 0.4848        | 27.0  | 15039 | 0.7740          | 0.7083   |
| 0.4801        | 28.0  | 15596 | 0.7761          | 0.7093   |
| 0.5059        | 29.0  | 16153 | 0.7776          | 0.7042   |
| 0.51          | 30.0  | 16710 | 0.7786          | 0.7073   |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0