---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- librispeech_asr
metrics:
- wer
model-index:
- name: whisper-small-libirClean-vs-commonNative-en
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: librispeech_asr
      type: librispeech_asr
      config: clean
      split: train
      args: clean
    metrics:
    - name: Wer
      type: wer
      value: 84.71153846153847
---

<!-- 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-libirClean-vs-commonNative-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: 2.3887
- Wer: 84.7115

## 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: 8
- 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: 10
- training_steps: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.2459        | 0.26  | 10   | 3.6972          | 20.6731 |
| 0.83          | 0.53  | 20   | 2.9120          | 33.1731 |
| 0.5312        | 0.79  | 30   | 2.4692          | 76.6346 |
| 0.445         | 1.05  | 40   | 2.3355          | 65.8654 |
| 0.3173        | 1.32  | 50   | 2.3887          | 84.7115 |


### Framework versions

- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2