---
language:
- eu
license: apache-2.0
base_model: openai/whisper-medium
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Medium 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: 9.200601844614663
---

<!-- 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_16_1 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4303
- Wer: 9.2006

## 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
- gradient_accumulation_steps: 4
- 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     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.0055        | 10.03  | 1000  | 0.2463          | 11.8425 |
| 0.003         | 20.05  | 2000  | 0.2638          | 11.3178 |
| 0.0018        | 30.08  | 3000  | 0.2837          | 10.9583 |
| 0.0009        | 40.1   | 4000  | 0.2768          | 10.4414 |
| 0.0008        | 50.13  | 5000  | 0.2880          | 10.1776 |
| 0.0012        | 60.15  | 6000  | 0.2903          | 10.0526 |
| 0.0002        | 70.18  | 7000  | 0.2909          | 9.8357  |
| 0.0013        | 80.2   | 8000  | 0.2766          | 9.9392  |
| 0.0001        | 90.23  | 9000  | 0.3110          | 9.3003  |
| 0.0           | 100.25 | 10000 | 0.3278          | 9.3315  |
| 0.0           | 110.28 | 11000 | 0.3393          | 9.3081  |
| 0.0           | 120.3  | 12000 | 0.3508          | 9.2993  |
| 0.0           | 130.33 | 13000 | 0.3617          | 9.3218  |
| 0.0           | 140.35 | 14000 | 0.3732          | 9.3354  |
| 0.0           | 150.38 | 15000 | 0.3849          | 9.3735  |
| 0.0           | 160.4  | 16000 | 0.3073          | 9.3335  |
| 0.0           | 170.43 | 17000 | 0.3320          | 9.3569  |
| 0.0           | 180.45 | 18000 | 0.3453          | 9.3022  |
| 0.0           | 190.48 | 19000 | 0.3561          | 9.3071  |
| 0.0           | 200.5  | 20000 | 0.3660          | 9.2983  |
| 0.0           | 210.53 | 21000 | 0.3755          | 9.2876  |
| 0.0           | 220.55 | 22000 | 0.3847          | 9.4976  |
| 0.0           | 230.58 | 23000 | 0.3940          | 9.5054  |
| 0.0           | 240.6  | 24000 | 0.4021          | 9.4703  |
| 0.0           | 250.63 | 25000 | 0.4126          | 9.4537  |
| 0.0           | 260.65 | 26000 | 0.3174          | 9.2758  |
| 0.0           | 270.68 | 27000 | 0.3444          | 9.2622  |
| 0.0           | 280.7  | 28000 | 0.3588          | 9.2084  |
| 0.0           | 290.73 | 29000 | 0.3698          | 9.3472  |
| 0.0           | 300.75 | 30000 | 0.3786          | 9.3423  |
| 0.0           | 310.78 | 31000 | 0.3868          | 9.3169  |
| 0.0           | 320.8  | 32000 | 0.3948          | 9.3286  |
| 0.0           | 330.83 | 33000 | 0.4018          | 9.3335  |
| 0.0           | 340.85 | 34000 | 0.4081          | 9.3286  |
| 0.0           | 350.88 | 35000 | 0.4138          | 9.3364  |
| 0.0           | 360.9  | 36000 | 0.4191          | 9.3432  |
| 0.0           | 370.93 | 37000 | 0.4234          | 9.3315  |
| 0.0           | 380.95 | 38000 | 0.4270          | 9.3403  |
| 0.0           | 390.98 | 39000 | 0.4294          | 9.2153  |
| 0.0           | 401.0  | 40000 | 0.4303          | 9.2006  |


### Framework versions

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