metadata
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
Whisper Medium Basque
This model is a fine-tuned version of 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