---
language:
- ca
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Base 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: 13.789654186910546
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Base Catalan

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_13_0 ca dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2782
- Wer: 13.7897

## 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: 2.5e-05
- train_batch_size: 128
- eval_batch_size: 64
- 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: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0975        | 3.05  | 1000 | 0.3560          | 19.4421 |
| 0.1381        | 7.04  | 2000 | 0.3066          | 16.1486 |
| 0.1302        | 11.04 | 3000 | 0.2902          | 15.4296 |
| 0.1089        | 15.03 | 4000 | 0.2699          | 14.0726 |
| 0.0505        | 19.03 | 5000 | 0.2782          | 13.7897 |


### Framework versions

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