transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer en dataset:LanugaugeLab 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:
- LanugaugeLab
metrics:
- wer
model-index:
- name: Whisper Small - LanguageLab V1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Language P1
      type: LanugaugeLab
      config: default
      split: train
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 31.753554502369667
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small - LanguageLab V1

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Language P1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1019
- Wer: 31.7536

## 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

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0001        | 21.28  | 1000 | 0.0898          | 43.6019 |
| 0.0           | 42.55  | 2000 | 0.0958          | 36.9668 |
| 0.0           | 63.83  | 3000 | 0.0991          | 35.0711 |
| 0.0           | 85.11  | 4000 | 0.1011          | 32.7014 |
| 0.0           | 106.38 | 5000 | 0.1019          | 31.7536 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu118
- Datasets 2.17.1
- Tokenizers 0.15.2