metadata
language:
- eu
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Tiny 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: 19.094888228857275
Whisper Tiny Basque
This model is a fine-tuned version of openai/whisper-tiny on the mozilla-foundation/common_voice_16_1 eu dataset. It achieves the following results on the evaluation set:
- Loss: 0.5146
- Wer: 19.0949
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: 3.75e-05
- train_batch_size: 256
- eval_batch_size: 128
- 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: 40000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0426 | 10.0 | 1000 | 0.3451 | 23.2003 |
| 0.0077 | 20.0 | 2000 | 0.4123 | 22.6053 |
| 0.0013 | 30.0 | 3000 | 0.4288 | 21.1965 |
| 0.0004 | 40.0 | 4000 | 0.4538 | 21.1926 |
| 0.0003 | 50.0 | 5000 | 0.4757 | 21.1808 |
| 0.0206 | 60.0 | 6000 | 0.4172 | 22.2751 |
| 0.0003 | 70.0 | 7000 | 0.4374 | 19.5131 |
| 0.0002 | 80.0 | 8000 | 0.4547 | 19.5091 |
| 0.0001 | 90.0 | 9000 | 0.4697 | 19.5062 |
| 0.0001 | 100.0 | 10000 | 0.4853 | 19.5199 |
| 0.0001 | 110.0 | 11000 | 0.5009 | 19.5687 |
| 0.0 | 120.0 | 12000 | 0.5175 | 19.6586 |
| 0.0 | 130.0 | 13000 | 0.5348 | 19.7729 |
| 0.0 | 140.0 | 14000 | 0.5531 | 19.7847 |
| 0.0002 | 150.0 | 15000 | 0.4626 | 19.4730 |
| 0.0001 | 160.0 | 16000 | 0.4813 | 19.2199 |
| 0.0 | 170.0 | 17000 | 0.4932 | 19.1691 |
| 0.0 | 180.0 | 18000 | 0.5041 | 19.1291 |
| 0.0 | 190.0 | 19000 | 0.5146 | 19.0949 |
| 0.0 | 200.0 | 20000 | 0.5254 | 19.1232 |
| 0.0 | 210.0 | 21000 | 0.5369 | 19.1369 |
| 0.0 | 220.0 | 22000 | 0.5484 | 19.1125 |
| 0.0 | 230.0 | 23000 | 0.5606 | 19.1330 |
| 0.0 | 240.0 | 24000 | 0.5732 | 19.1965 |
| 0.0 | 250.0 | 25000 | 0.5864 | 19.2219 |
| 0.0 | 260.0 | 26000 | 0.6003 | 19.3108 |
| 0.0 | 270.0 | 27000 | 0.6140 | 19.3714 |
| 0.0034 | 280.0 | 28000 | 0.5536 | 20.6630 |
| 0.0 | 290.0 | 29000 | 0.5486 | 19.3391 |
| 0.0 | 300.0 | 30000 | 0.5591 | 19.3059 |
| 0.0 | 310.0 | 31000 | 0.5669 | 19.3137 |
| 0.0 | 320.0 | 32000 | 0.5737 | 19.3225 |
| 0.0 | 330.0 | 33000 | 0.5798 | 19.2883 |
| 0.0 | 340.0 | 34000 | 0.5856 | 19.2668 |
| 0.0 | 350.0 | 35000 | 0.5911 | 19.2346 |
| 0.0 | 360.0 | 36000 | 0.5962 | 19.2287 |
| 0.0 | 370.0 | 37000 | 0.6010 | 19.2326 |
| 0.0 | 380.0 | 38000 | 0.6050 | 19.2287 |
| 0.0 | 390.0 | 39000 | 0.6081 | 19.2375 |
| 0.0 | 400.0 | 40000 | 0.6095 | 19.1965 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1