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rishabhjain16
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whisper_medium_en_to_pf10h

Automatic Speech Recognition
Transformers
PyTorch
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whisper
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whisper_medium_en_to_pf10h
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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-medium.en
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/infer_cmu_9h
      type: rishabhjain16/infer_cmu_9h
      config: en
      split: test
    metrics:
    - type: wer
      value: 15.53
      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: 3.14
      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: 15.84
      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: 5.28
      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.en

This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1748
- Wer: 2.7097

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0329        | 5.0   | 500  | 0.1343          | 4.0125 |
| 0.0013        | 10.01 | 1000 | 0.1531          | 2.8810 |
| 0.0002        | 15.01 | 1500 | 0.1609          | 2.7321 |
| 0.0002        | 20.01 | 2000 | 0.1608          | 2.7544 |
| 0.0001        | 25.01 | 2500 | 0.1688          | 2.7321 |
| 0.0002        | 30.02 | 3000 | 0.1722          | 2.7172 |
| 0.0001        | 35.02 | 3500 | 0.1742          | 2.7172 |
| 0.0001        | 40.02 | 4000 | 0.1748          | 2.7097 |


### Framework versions

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