---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-large-v2
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/infer_myst
      type: rishabhjain16/infer_myst
      config: en
      split: test
    metrics:
    - type: wer
      value: 11.62
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/infer_pfs
      type: rishabhjain16/infer_pfs
      config: en
      split: test
    metrics:
    - type: wer
      value: 2.84
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/infer_cmu
      type: rishabhjain16/infer_cmu
      config: en
      split: test
    metrics:
    - type: wer
      value: 1.75
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/libritts_dev_clean
      type: rishabhjain16/libritts_dev_clean
      config: en
      split: test
    metrics:
    - type: wer
      value: 4.53
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/infer_pf_swedish
      type: rishabhjain16/infer_pf_swedish
      config: en
      split: test
    metrics:
    - type: wer
      value: 8.36
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/infer_pf_german
      type: rishabhjain16/infer_pf_german
      config: en
      split: test
    metrics:
    - type: wer
      value: 34.26
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/infer_pf_italian
      type: rishabhjain16/infer_pf_italian
      config: en
      split: test
    metrics:
    - type: wer
      value: 4.4
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/infer_so_chinese
      type: rishabhjain16/infer_so_chinese
      config: en
      split: test
    metrics:
    - type: wer
      value: 14.52
      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. -->

# openai/whisper-large-v2

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1969
- Wer: 9.3970

## 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: 32
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6144        | 0.12  | 500  | 0.2795          | 14.0737 |
| 0.1643        | 0.25  | 1000 | 0.2213          | 11.4916 |
| 0.2175        | 0.38  | 1500 | 0.2009          | 10.0021 |
| 0.1512        | 1.11  | 2000 | 0.1980          | 11.2632 |
| 0.1527        | 1.24  | 2500 | 0.1916          | 10.8469 |
| 0.0918        | 1.36  | 3000 | 0.1890          | 9.6498  |
| 0.047         | 2.1   | 3500 | 0.2034          | 9.4274  |
| 0.0822        | 2.23  | 4000 | 0.1969          | 9.3970  |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2