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---
language:
- eu
license: apache-2.0
base_model: openai/whisper-medium
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Medium 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: 14.119648426424725
---

<!-- 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 Medium Basque

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_13_0 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4119
- Wer: 14.1196

## 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: 64
- eval_batch_size: 32
- 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: 10000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0206        | 4.02  | 1000  | 0.2998          | 16.9995 |
| 0.0036        | 9.01  | 2000  | 0.3235          | 15.5211 |
| 0.0018        | 14.01 | 3000  | 0.3454          | 14.9905 |
| 0.0013        | 19.01 | 4000  | 0.3538          | 14.9439 |
| 0.0013        | 24.01 | 5000  | 0.3587          | 14.8568 |
| 0.0002        | 29.0  | 6000  | 0.3799          | 14.4153 |
| 0.0001        | 33.02 | 7000  | 0.3937          | 14.2067 |
| 0.0001        | 38.02 | 8000  | 0.4050          | 14.1946 |
| 0.0001        | 43.01 | 9000  | 0.4119          | 14.1196 |
| 0.0001        | 48.01 | 10000 | 0.4150          | 14.1358 |


### Framework versions

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