---
license: apache-2.0
tags:
- generated_from_trainer
- hf-asr-leaderboard
- whisper-event
metrics:
- wer
model-index:
- name: openai/whisper-medium
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 ca
      type: mozilla-foundation/common_voice_11_0
      args: 'config: ml, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 8.282966640983934
---

<!-- 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 is an automatic speech recognition model that also does punctuation and casing. This model is for research only, **we do not recommend using this model on production environments**. See our [learnings](https://huggingface.co/softcatala/whisper-small-ca/blob/main/TRAINING.md) when training these models.


This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 ca dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2029
- Wer: 8.3235

## 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: 2
- eval_batch_size: 1
- 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: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.2652        | 0.1   | 2000  | 0.3469          | 15.3537 |
| 0.3273        | 0.2   | 4000  | 0.3151          | 14.1141 |
| 0.2696        | 0.3   | 6000  | 0.2955          | 13.2472 |
| 0.1725        | 0.4   | 8000  | 0.2787          | 11.6834 |
| 0.1741        | 0.5   | 10000 | 0.2648          | 11.0088 |
| 0.2037        | 0.6   | 12000 | 0.2470          | 10.1909 |
| 0.1586        | 0.7   | 14000 | 0.2333          | 9.4096  |
| 0.1548        | 0.8   | 16000 | 0.2184          | 8.9724  |
| 0.1799        | 1.08  | 18000 | 0.2064          | 8.2830  |
| 0.1165        | 1.18  | 20000 | 0.2029          | 8.3235  |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.10.0+cu102
- Datasets 2.7.1
- Tokenizers 0.13.2