---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_9_0
metrics:
- wer
model-index:
- name: yt-special-batch8-base
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_9_0 id
      type: mozilla-foundation/common_voice_9_0
      config: id
      split: train
      args: id
    metrics:
    - name: Wer
      type: wer
      value: 11.4438961596224
---

<!-- 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. -->

# yt-special-batch8-base

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_9_0 id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4155
- Wer: 11.4439

## 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: 4
- 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      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 41.113        | 1.58  | 1000 | 42.9759         | 107.5628 |
| 17.3442       | 3.17  | 2000 | 18.7037         | 144.1064 |
| 10.8061       | 4.75  | 3000 | 7.1531          | 52.5510  |
| 3.3269        | 6.34  | 4000 | 3.1035          | 47.0586  |
| 0.7405        | 7.92  | 5000 | 0.4155          | 11.4439  |


### Framework versions

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