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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- librispeech_asr
metrics:
- wer
base_model: openai/whisper-small
model-index:
- name: whisper-small-en
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: librispeech_asr
      type: librispeech_asr
      config: clean
      split: test
      args: clean
    metrics:
    - type: wer
      value: 124.51154529307283
      name: Wer
---

<!-- 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-en

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the librispeech_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 6.7832
- Wer: 124.5115

## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer       |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 9.6259        | 1.57  | 5    | 10.7408         | 1127.3535 |
| 11.5288       | 3.29  | 10   | 9.2534          | 100.0     |
| 10.9249       | 4.86  | 15   | 7.8357          | 100.0     |
| 7.0442        | 6.57  | 20   | 6.9971          | 595.3819  |
| 8.6762        | 8.29  | 25   | 5.6135          | 312.2558  |
| 5.4239        | 9.86  | 30   | 5.4885          | 97.1581   |
| 4.986         | 11.57 | 35   | 5.2888          | 628.7744  |
| 6.708         | 13.29 | 40   | 4.9665          | 277.6199  |
| 3.9096        | 14.86 | 45   | 5.0861          | 631.9716  |
| 3.2326        | 16.57 | 50   | 5.0090          | 279.7513  |
| 3.9691        | 18.29 | 55   | 5.0804          | 133.2149  |
| 1.8661        | 19.86 | 60   | 5.4423          | 317.5844  |
| 1.1588        | 21.57 | 65   | 5.7955          | 119.5382  |
| 1.0355        | 23.29 | 70   | 6.0458          | 190.2309  |
| 0.3455        | 24.86 | 75   | 6.3057          | 106.7496  |
| 0.142         | 26.57 | 80   | 6.5767          | 209.9467  |
| 0.1722        | 28.29 | 85   | 6.5937          | 101.4210  |
| 0.0816        | 29.86 | 90   | 6.7679          | 149.7336  |
| 0.079         | 31.57 | 95   | 6.8008          | 133.5702  |
| 0.1007        | 33.29 | 100  | 6.7832          | 124.5115  |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2