---
language:
- eu
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 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: 11.339057880027543
---

<!-- 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 Large-V2 Basque

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 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3943
- Wer: 11.3391

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0355        | 4.01  | 1000  | 0.2616          | 14.8224 |
| 0.0079        | 9.01  | 2000  | 0.2777          | 13.5202 |
| 0.0041        | 14.01 | 3000  | 0.2764          | 12.7364 |
| 0.0047        | 19.0  | 4000  | 0.2932          | 12.6939 |
| 0.004         | 24.0  | 5000  | 0.2969          | 12.7992 |
| 0.0019        | 29.0  | 6000  | 0.3066          | 12.6008 |
| 0.004         | 33.01 | 7000  | 0.2973          | 12.6696 |
| 0.0007        | 38.01 | 8000  | 0.3253          | 12.2686 |
| 0.0006        | 43.01 | 9000  | 0.3391          | 12.5319 |
| 0.0009        | 48.01 | 10000 | 0.3303          | 12.2767 |
| 0.0004        | 53.0  | 11000 | 0.3383          | 12.0195 |
| 0.0003        | 58.0  | 12000 | 0.3398          | 11.7441 |
| 0.0005        | 63.0  | 13000 | 0.3396          | 11.8778 |
| 0.0001        | 67.01 | 14000 | 0.3544          | 11.6469 |
| 0.0           | 72.01 | 15000 | 0.3752          | 11.4160 |
| 0.0           | 77.01 | 16000 | 0.3860          | 11.3411 |
| 0.0           | 82.01 | 17000 | 0.3943          | 11.3391 |
| 0.0           | 87.0  | 18000 | 0.4013          | 11.3532 |
| 0.0           | 92.0  | 19000 | 0.4063          | 11.3613 |
| 0.0           | 97.0  | 20000 | 0.4086          | 11.3512 |


### Framework versions

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