transformers pytorch whisper automatic-speech-recognition whisper-event generated_from_trainer ca dataset:mozilla-foundation/common_voice_13_0 base_model:openai/whisper-large-v2 license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- ca
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large-V2 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: 4.671620462989425
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Large-V2 Catalan

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_13_0 ca dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1494
- Wer: 4.6716

## 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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.1072        | 1.02  | 1000  | 0.1637          | 7.0329 |
| 0.0239        | 3.02  | 2000  | 0.1784          | 7.0277 |
| 0.0507        | 5.02  | 3000  | 0.1754          | 6.5773 |
| 0.0571        | 7.02  | 4000  | 0.1620          | 6.5047 |
| 0.0193        | 9.02  | 5000  | 0.1821          | 6.4887 |
| 0.0625        | 11.02 | 6000  | 0.1443          | 6.7585 |
| 0.0752        | 13.02 | 7000  | 0.1653          | 5.9097 |
| 0.0359        | 15.02 | 8000  | 0.1406          | 5.8760 |
| 0.0565        | 17.01 | 9000  | 0.1496          | 5.9680 |
| 0.0196        | 19.01 | 10000 | 0.1788          | 5.2746 |
| 0.0215        | 21.01 | 11000 | 0.1539          | 5.3895 |
| 0.0178        | 23.01 | 12000 | 0.1800          | 5.3764 |
| 0.0114        | 25.01 | 13000 | 0.1709          | 5.2078 |
| 0.0123        | 27.01 | 14000 | 0.1827          | 5.2003 |
| 0.0337        | 29.01 | 15000 | 0.1553          | 5.3655 |
| 0.0108        | 31.01 | 16000 | 0.1476          | 4.9151 |
| 0.0194        | 33.01 | 17000 | 0.1396          | 4.8477 |
| 0.0472        | 35.0  | 18000 | 0.1202          | 4.8717 |
| 0.0401        | 37.0  | 19000 | 0.1494          | 4.6716 |
| 0.0127        | 39.0  | 20000 | 0.1187          | 4.7276 |


### Framework versions

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