---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-tiny-fa
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: fa
      split: None
      args: fa
    metrics:
    - name: Wer
      type: wer
      value: 51.8555393407073
---

<!-- 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-tiny-fa

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5542
- Wer: 51.8555

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 5000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5002        | 0.8110 | 1000 | 0.7493          | 67.9014 |
| 0.3239        | 1.6221 | 2000 | 0.6166          | 58.6680 |
| 0.2198        | 2.4331 | 3000 | 0.5782          | 54.3310 |
| 0.1695        | 3.2441 | 4000 | 0.5619          | 52.7925 |
| 0.1309        | 4.0552 | 5000 | 0.5542          | 51.8555 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1