---
base_model: openai/whisper-small
library_name: transformers
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: names-whisper-en-spectrogram-pitch-shifted
  results: []
---

<!-- 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. -->

# names-whisper-en-spectrogram-pitch-shifted

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2384
- Ner percent: 101.9340
- Wer: 5.3520

## 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Ner percent | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:-----------:|:------:|
| 0.036         | 5.0251  | 1000 | 0.2288          | 99.9682     | 6.2317 |
| 0.0013        | 10.0503 | 2000 | 0.2292          | 97.7273     | 5.6542 |
| 0.0005        | 15.0754 | 3000 | 0.2334          | 102.4688    | 5.3084 |
| 0.0003        | 20.1005 | 4000 | 0.2368          | 101.9340    | 5.3621 |
| 0.0003        | 25.1256 | 5000 | 0.2384          | 101.9340    | 5.3520 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1