transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer en dataset:kiriku/Homophones_filted_dataset base_model:openai/whisper-small license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- kiriku/Homophones_filted_dataset
metrics:
- wer
model-index:
- name: Homophones_filted_dataset Whisper base en
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: 'Homophones in Common Voice 15.0 '
      type: kiriku/Homophones_filted_dataset
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 22.51904761904762
---

<!-- 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. -->

# Homophones_filted_dataset Whisper base en

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Homophones in Common Voice 15.0  dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4026
- Wer: 22.5190

## 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3224        | 0.25  | 1000 | 0.4419          | 24.7690 |
| 0.3445        | 0.5   | 2000 | 0.4162          | 23.0405 |
| 0.3141        | 0.75  | 3000 | 0.4077          | 22.9357 |
| 0.3017        | 1.0   | 4000 | 0.4026          | 22.5190 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0
