---
library_name: transformers
language:
- ps
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- ihanif/common_voice_ps_20_0
model-index:
- name: Whisper small Ps - ZFA
  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 Ps - ZFA

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 20.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8066

## 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-05
- train_batch_size: 1
- eval_batch_size: 1
- 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
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.7874        | 0.1856 | 500  | 1.3995          |
| 1.3066        | 0.3712 | 1000 | 1.2622          |
| 1.1437        | 0.5568 | 1500 | 1.1273          |
| 1.0676        | 0.7424 | 2000 | 1.0547          |
| 1.0014        | 0.9280 | 2500 | 0.9770          |
| 0.7683        | 1.1136 | 3000 | 0.9779          |
| 0.6386        | 1.2992 | 3500 | 0.9486          |
| 0.6103        | 1.4848 | 4000 | 0.9071          |
| 0.599         | 1.6704 | 4500 | 0.8748          |
| 0.5665        | 1.8560 | 5000 | 0.8525          |
| 0.5032        | 2.0416 | 5500 | 0.8532          |
| 0.2884        | 2.2272 | 6000 | 0.8503          |
| 0.269         | 2.4128 | 6500 | 0.8316          |
| 0.2784        | 2.5984 | 7000 | 0.8137          |
| 0.236         | 2.7840 | 7500 | 0.8227          |
| 0.2543        | 2.9696 | 8000 | 0.8066          |


### Framework versions

- Transformers 4.56.2
- Pytorch 2.7.0+cu126
- Datasets 4.1.1
- Tokenizers 0.22.0