transformers pytorch whisper automatic-speech-recognition whisper-event generated_from_trainer eu dataset:mozilla-foundation/common_voice_13_0 base_model:openai/whisper-large license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- eu
license: apache-2.0
base_model: openai/whisper-large
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large Basque
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_13_0 eu
      type: mozilla-foundation/common_voice_13_0
      config: eu
      split: test
      args: eu
    metrics:
    - name: Wer
      type: wer
      value: 12.234193365466401
---

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

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_13_0 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4369
- Wer: 12.2342

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0196        | 4.01  | 1000  | 0.2825          | 15.4725 |
| 0.0039        | 9.01  | 2000  | 0.3072          | 14.2270 |
| 0.0031        | 14.01 | 3000  | 0.3170          | 13.7652 |
| 0.0023        | 19.0  | 4000  | 0.3310          | 13.6640 |
| 0.0014        | 24.0  | 5000  | 0.3384          | 13.5749 |
| 0.0034        | 29.0  | 6000  | 0.3425          | 13.7450 |
| 0.0011        | 33.01 | 7000  | 0.3476          | 13.0990 |
| 0.001         | 38.01 | 8000  | 0.3432          | 13.0990 |
| 0.0004        | 43.01 | 9000  | 0.3524          | 12.8033 |
| 0.0017        | 48.01 | 10000 | 0.3620          | 13.3946 |
| 0.0003        | 53.0  | 11000 | 0.3564          | 12.6190 |
| 0.0001        | 58.0  | 12000 | 0.3675          | 12.6352 |
| 0.0           | 63.0  | 13000 | 0.3878          | 12.4286 |
| 0.0           | 67.01 | 14000 | 0.3996          | 12.3577 |
| 0.0           | 72.01 | 15000 | 0.4088          | 12.3456 |
| 0.0           | 77.01 | 16000 | 0.4167          | 12.3091 |
| 0.0           | 82.01 | 17000 | 0.4241          | 12.3112 |
| 0.0           | 87.0  | 18000 | 0.4302          | 12.3193 |
| 0.0           | 92.0  | 19000 | 0.4351          | 12.2565 |
| 0.0           | 97.0  | 20000 | 0.4369          | 12.2342 |


### Framework versions

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