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_myst
      type: rishabhjain16/infer_myst
      config: en
      split: test
    metrics:
    - type: wer
      value: 12.37
      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: 23.62
      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: 2.32
      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: 180.79
      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: 211.01
      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: 184.24
      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: 48.34
      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: 4.81
      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: 0.2381
- Wer: 11.1244

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3639        | 0.12  | 500  | 0.2512          | 12.9597 |
| 0.1931        | 0.25  | 1000 | 0.2123          | 12.1414 |
| 0.329         | 1.08  | 1500 | 0.2064          | 11.5818 |
| 0.097         | 1.21  | 2000 | 0.2050          | 10.9775 |
| 0.0522        | 2.04  | 2500 | 0.2258          | 10.4390 |
| 0.1026        | 2.17  | 3000 | 0.2201          | 11.7017 |
| 0.0448        | 3.0   | 3500 | 0.2287          | 10.3873 |
| 0.0455        | 3.13  | 4000 | 0.2381          | 11.1244 |


### Framework versions

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