transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer dataset:common_voice_11_0 base_model:openai/whisper-small license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: openai/whisper-small
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: ta
      split: test
      args: ta
    metrics:
    - name: Wer
      type: wer
      value: 11.131213479231658
---

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# openai/whisper-small

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2355
- Wer: 11.1312

## 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 | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2049        | 0.68  | 1000 | 0.2570          | 13.7607 |
| 0.1396        | 1.36  | 2000 | 0.2318          | 12.1079 |
| 0.0807        | 2.04  | 3000 | 0.2272          | 11.3533 |
| 0.085         | 2.72  | 4000 | 0.2242          | 11.1542 |
| 0.0483        | 3.4   | 5000 | 0.2355          | 11.1312 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
