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

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: 0.0374
- Ner percent: 98.7838
- Wer: 0.8407

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:-----------:|:------:|
| 0.0039        | 5.0505  | 1000 | 0.0352          | 97.8378     | 1.1843 |
| 0.0005        | 10.1010 | 2000 | 0.0350          | 98.9189     | 0.8674 |
| 0.0003        | 15.1515 | 3000 | 0.0361          | 98.7838     | 0.8340 |
| 0.0002        | 20.2020 | 4000 | 0.0370          | 98.7838     | 0.8373 |
| 0.0002        | 25.2525 | 5000 | 0.0374          | 98.7838     | 0.8407 |


### Framework versions

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