---
base_model: openai/whisper-small
library_name: transformers
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper-squeezeformer-v3
  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-v3

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: 0.1511
- Wer: 6.8035

## 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: 2500
- training_steps: 30000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer      |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 4.8718        | 1.0   | 2500  | 3.8609          | 111.8590 |
| 2.5628        | 2.0   | 5000  | 0.2978          | 15.6193  |
| 0.1698        | 3.0   | 7500  | 0.2218          | 11.0906  |
| 0.0867        | 4.0   | 10000 | 0.2011          | 10.1891  |
| 0.1697        | 5.0   | 12500 | 0.1641          | 8.9851   |
| 0.0993        | 6.0   | 15000 | 0.1553          | 7.8039   |
| 0.0651        | 7.0   | 17500 | 0.1555          | 7.2448   |
| 0.0468        | 8.0   | 20000 | 0.1569          | 7.1497   |
| 0.2168        | 9.0   | 22500 | 0.1509          | 7.0507   |
| 0.1467        | 10.0  | 25000 | 0.1494          | 6.9671   |
| 0.1113        | 11.0  | 27500 | 0.1493          | 6.7597   |
| 0.0914        | 12.0  | 30000 | 0.1511          | 6.8035   |


### Framework versions

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