README.md

---
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_so_chinese
      type: rishabhjain16/infer_so_chinese
      config: en
      split: test
    metrics:
    - type: wer
      value: 13.83
      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: 31.46
      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: 3.98
      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: 7.24
      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: 4.47
      name: WER
  - 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: 11.6
      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: 9.22
      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: 3.09
      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: 0.2637
- Wer: 10.1437

## 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: 16
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2612        | 0.12  | 500  | 0.2687          | 12.4717 |
| 0.5072        | 0.25  | 1000 | 0.2606          | 12.2762 |
| 0.1023        | 1.05  | 1500 | 0.2436          | 10.0626 |
| 0.1379        | 1.18  | 2000 | 0.2447          | 11.1944 |
| 0.1237        | 1.3   | 2500 | 0.2412          | 11.0989 |
| 0.0684        | 2.11  | 3000 | 0.2715          | 10.2703 |
| 0.0925        | 2.23  | 3500 | 0.2553          | 10.2648 |
| 0.1484        | 3.03  | 4000 | 0.2637          | 10.1437 |


### Framework versions

- Transformers 4.29.0
- Pytorch 1.14.0a0+44dac51
- Datasets 2.12.0
- Tokenizers 0.13.3