whisper-base-ps / README.md
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---
library_name: transformers
language:
- ps
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- SherwinDesouza/pashto-common-voice-20
metrics:
- wer
model-index:
- name: Whisper Base Ps - ZFA
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 20.0
type: SherwinDesouza/pashto-common-voice-20
args: 'config: ps, split: test'
metrics:
- name: Wer
type: wer
value: 54.07066052227343
---
<!-- 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 Base Ps - ZFA
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 20.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6856
- Wer: 54.0707
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2602 | 5.9199 | 1000 | 0.6856 | 54.0707 |
### Framework versions
- Transformers 4.53.2
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2