---
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-small
metrics:
- wer
model-index:
- name: names-whisper-en-spectrogram-original
  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-original

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: 0.1720
- Ner percent: 105.0286
- Wer: 5.9900

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:-----------:|:------:|
| 0.0081        | 5.1546  | 1000 | 0.1413          | 104.8314    | 5.9866 |
| 0.0017        | 10.3093 | 2000 | 0.1528          | 104.7256    | 5.8949 |
| 0.0007        | 15.4639 | 3000 | 0.1628          | 105.3074    | 5.9764 |
| 0.0005        | 20.6186 | 4000 | 0.1690          | 104.9219    | 5.9764 |
| 0.0004        | 25.7732 | 5000 | 0.1720          | 105.0286    | 5.9900 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1