---
language:
- ca
license: apache-2.0
base_model: openai/whisper-medium
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Medium Catalan
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_13_0 ca
      type: mozilla-foundation/common_voice_13_0
      config: ca
      split: test
      args: ca
    metrics:
    - name: Wer
      type: wer
      value: 5.995427264932838
---

<!-- 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. -->

# Whisper Medium Catalan

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_13_0 ca dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1434
- Wer: 5.9954

## 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: 64
- 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: 10000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.1158        | 1.05  | 1000  | 0.1846          | 8.3630 |
| 0.0184        | 3.05  | 2000  | 0.2017          | 8.0629 |
| 0.0522        | 5.04  | 3000  | 0.1940          | 8.1177 |
| 0.0595        | 7.04  | 4000  | 0.1742          | 7.4696 |
| 0.0179        | 9.04  | 5000  | 0.1899          | 7.3095 |
| 0.0646        | 11.04 | 6000  | 0.1555          | 6.3441 |
| 0.0825        | 13.03 | 7000  | 0.1810          | 6.4841 |
| 0.0309        | 15.03 | 8000  | 0.1464          | 6.3544 |
| 0.0695        | 17.03 | 9000  | 0.1434          | 5.9954 |
| 0.0186        | 19.03 | 10000 | 0.1706          | 6.1097 |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3