---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-medium
  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: 11.72
      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: 3.11
      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: 2.36
      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: 16.72
      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: 86.13
      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: 23.94
      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: 27.88
      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: 5.62
      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-medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2775
- Wer: 9.7168

## 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: 32
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2572        | 0.12  | 500  | 0.2180          | 10.4499 |
| 0.1542        | 1.08  | 1000 | 0.1995          | 10.2143 |
| 0.062         | 2.04  | 1500 | 0.2177          | 10.2560 |
| 0.0761        | 2.16  | 2000 | 0.2013          | 11.0693 |
| 0.0193        | 3.12  | 2500 | 0.2318          | 10.0235 |
| 0.0065        | 4.07  | 3000 | 0.2591          | 9.9646  |
| 0.0123        | 5.03  | 3500 | 0.2760          | 9.7453  |
| 0.0039        | 5.15  | 4000 | 0.2775          | 9.7168  |


### Framework versions

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