---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- wwwtwwwt/fineaudio-NewsPolitics
metrics:
- wer
model-index:
- name: Whisper Tiny En - NewsPolitics - Social Commentary
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fineaudio-NewsPolitics-Social Commentary
      type: wwwtwwwt/fineaudio-NewsPolitics
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 52.65511043774045
---

<!-- 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 En - NewsPolitics - Social Commentary

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fineaudio-NewsPolitics-Social Commentary dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9274
- Wer: 52.6551

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.8927        | 0.5705 | 1000 | 1.0172          | 59.8874 |
| 0.702         | 1.1409 | 2000 | 0.9510          | 56.5795 |
| 0.6797        | 1.7114 | 3000 | 0.9338          | 55.1387 |
| 0.6021        | 2.2818 | 4000 | 0.9274          | 52.6551 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0