---
language:
- eu
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
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_16_1 eu
      type: mozilla-foundation/common_voice_16_1
      config: eu
      split: test
      args: eu
    metrics:
    - name: Wer
      type: wer
      value: 7.720415819915585
---

<!-- 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_16_1 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4206
- Wer: 7.7204

## 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: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 40000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.0112        | 10.04  | 1000  | 0.2182          | 10.1571 |
| 0.0052        | 20.08  | 2000  | 0.2372          | 9.6276  |
| 0.0017        | 30.11  | 3000  | 0.2417          | 9.0150  |
| 0.0022        | 40.15  | 4000  | 0.2341          | 8.8938  |
| 0.0023        | 50.19  | 5000  | 0.2451          | 8.9388  |
| 0.0006        | 60.23  | 6000  | 0.2517          | 8.4161  |
| 0.0006        | 70.26  | 7000  | 0.2499          | 8.0985  |
| 0.0008        | 80.3   | 8000  | 0.2548          | 8.3467  |
| 0.0004        | 90.34  | 9000  | 0.2498          | 7.9559  |
| 0.0003        | 100.38 | 10000 | 0.2489          | 7.6940  |
| 0.0           | 110.41 | 11000 | 0.2906          | 7.5455  |
| 0.0           | 120.45 | 12000 | 0.3027          | 7.4596  |
| 0.0           | 130.49 | 13000 | 0.3137          | 7.4517  |
| 0.0           | 140.53 | 14000 | 0.3243          | 7.4644  |
| 0.0           | 150.56 | 15000 | 0.3351          | 7.4762  |
| 0.0           | 160.6  | 16000 | 0.3459          | 7.4556  |
| 0.0           | 170.64 | 17000 | 0.3565          | 7.4605  |
| 0.0           | 180.68 | 18000 | 0.3689          | 7.4996  |
| 0.0           | 190.72 | 19000 | 0.3806          | 7.5934  |
| 0.0           | 200.75 | 20000 | 0.3912          | 7.6344  |
| 0.0           | 210.79 | 21000 | 0.4005          | 7.5485  |
| 0.0           | 220.83 | 22000 | 0.4102          | 7.6266  |
| 0.0079        | 230.87 | 23000 | 0.2467          | 9.1654  |
| 0.0           | 240.9  | 24000 | 0.3097          | 7.7615  |
| 0.0           | 250.94 | 25000 | 0.3311          | 7.7243  |
| 0.0           | 260.98 | 26000 | 0.3446          | 7.7028  |
| 0.0           | 271.02 | 27000 | 0.3551          | 7.7546  |
| 0.0           | 281.05 | 28000 | 0.3646          | 7.7986  |
| 0.0           | 291.09 | 29000 | 0.3729          | 7.7781  |
| 0.0           | 301.13 | 30000 | 0.3811          | 7.7634  |
| 0.0           | 311.17 | 31000 | 0.3878          | 7.7702  |
| 0.0           | 321.2  | 32000 | 0.3948          | 7.7722  |
| 0.0           | 331.24 | 33000 | 0.4003          | 7.7302  |
| 0.0           | 341.28 | 34000 | 0.4058          | 7.7312  |
| 0.0           | 351.32 | 35000 | 0.4108          | 7.7292  |
| 0.0           | 361.36 | 36000 | 0.4142          | 7.7321  |
| 0.0           | 371.39 | 37000 | 0.4170          | 7.7204  |
| 0.0           | 381.43 | 38000 | 0.4189          | 7.7253  |
| 0.0           | 391.47 | 39000 | 0.4202          | 7.7263  |
| 0.0           | 401.51 | 40000 | 0.4206          | 7.7204  |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1