---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- librispeech-clean
metrics:
- wer
model-index:
- name: Whisper Small English 1h
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Librispeech
      type: librispeech-clean
      config: default
      split: None
      args: 'config: english, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 53.45675203126608
---

<!-- 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 Small English 1h

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: 1.8110
- Wer: 53.4568

## 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-07
- 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: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0582        | 10.0  | 200  | 1.8847          | 56.4620 |
| 0.0495        | 20.0  | 400  | 1.8598          | 55.1579 |
| 0.042         | 30.0  | 600  | 1.8303          | 54.2240 |
| 0.0309        | 40.0  | 800  | 1.8152          | 53.7118 |
| 0.0323        | 50.0  | 1000 | 1.8110          | 53.4568 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1