---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper-squeezeformer-NSQU-whisper-sparse-A
  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. -->

# Whisper-squeezeformer-NSQU-whisper-sparse-A

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the LibriSpeech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1860
- Wer: 9.1296

## 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: 20
- 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: 3000
- training_steps: 36000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer      |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 3.89          | 1.0   | 3000  | 3.2878          | 114.5015 |
| 1.1579        | 2.0   | 6000  | 0.7947          | 42.0578  |
| 0.3888        | 3.0   | 9000  | 0.7379          | 36.9314  |
| 0.2242        | 4.0   | 12000 | 0.7417          | 35.9172  |
| 0.5221        | 5.0   | 15000 | 0.6811          | 32.7808  |
| 0.324         | 6.0   | 18000 | 0.6716          | 32.0457  |
| 0.2034        | 7.0   | 21000 | 0.6845          | 32.0073  |
| 0.2177        | 9.6   | 24000 | 0.1991          | 10.8624  |
| 0.127         | 10.8  | 27000 | 0.1856          | 10.5485  |
| 0.0909        | 12.0  | 30000 | 0.1838          | 9.5918   |
| 0.0785        | 13.2  | 33000 | 0.1849          | 9.1030   |
| 0.0595        | 14.4  | 36000 | 0.1860          | 9.1296   |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0