---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- yt
metrics:
- wer
model-index:
- name: special2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: yt id
      type: yt
      args: id
    metrics:
    - name: Wer
      type: wer
      value: 41.8877716509893
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# special2

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the yt id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6621
- Wer: 41.8878

## 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: 12
- eval_batch_size: 6
- 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: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.8117        | 0.26  | 1000 | 0.8215          | 48.6085 |
| 0.7087        | 0.52  | 2000 | 0.7323          | 52.3062 |
| 0.7057        | 0.77  | 3000 | 0.6922          | 50.0032 |
| 0.5319        | 1.03  | 4000 | 0.6686          | 42.1213 |
| 0.4704        | 1.29  | 5000 | 0.6621          | 41.8878 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3