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---
library_name: transformers
language:
- fa
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper small- Mohammad Khosravi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: fa
split: None
args: 'config: fa, split: test'
metrics:
- name: Wer
type: wer
value: 105.3763440860215
---
<!-- 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- Mohammad Khosravi
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0832
- Wer: 105.3763
## 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: 8
- 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: 5
- training_steps: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log | 1.4286 | 10 | 1.9791 | 109.6774 |
| No log | 2.8571 | 20 | 1.6973 | 107.5269 |
| 1.023 | 4.2857 | 30 | 1.6941 | 109.6774 |
| 1.023 | 5.7143 | 40 | 1.7788 | 107.5269 |
| 0.1444 | 7.1429 | 50 | 1.8726 | 104.3011 |
| 0.1444 | 8.5714 | 60 | 1.9535 | 103.2258 |
| 0.1444 | 10.0 | 70 | 1.9987 | 104.3011 |
| 0.0166 | 11.4286 | 80 | 2.0563 | 102.1505 |
| 0.0166 | 12.8571 | 90 | 2.0768 | 105.3763 |
| 0.0062 | 14.2857 | 100 | 2.0832 | 105.3763 |
### Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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