metadata
language:
- gl
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Tiny Galician
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0 gl
type: mozilla-foundation/common_voice_13_0
config: gl
split: test
args: gl
metrics:
- name: Wer
type: wer
value: 26.35037251655629
Whisper Tiny Galician
This model is a fine-tuned version of openai/whisper-tiny on the mozilla-foundation/common_voice_13_0 gl dataset. It achieves the following results on the evaluation set:
- Loss: 0.5832
- Wer: 26.3504
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: 5000
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0062 | 19.01 | 1000 | 0.5832 | 26.3504 |
0.0012 | 39.01 | 2000 | 0.6527 | 26.7177 |
0.0006 | 59.01 | 3000 | 0.6950 | 27.4352 |
0.0004 | 79.01 | 4000 | 0.7260 | 28.4044 |
0.0003 | 99.01 | 5000 | 0.7315 | 28.1905 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3