metadata
language:
- pl
library_name: peft
tags:
- generated_from_trainer
base_model: openai/whisper-base
datasets:
- mozilla-foundation/common_voice_17_0
model-index:
- name: Whisper Base Polish PEFT - s22678 prod
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
split: test
metrics:
- type: wer
value: 42.070773263433814
name: WER
Whisper Base Polish PEFT - s22678 prod
This model is a fine-tuned version of openai/openai/whisper-base on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5546
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: 0.001
- train_batch_size: 52
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.3265 | 1.0 | 400 | 0.4049 |
0.2506 | 2.01 | 800 | 0.3920 |
0.185 | 3.01 | 1200 | 0.3868 |
0.1506 | 4.01 | 1600 | 0.3859 |
0.1217 | 5.01 | 2000 | 0.3856 |
0.0931 | 6.02 | 2400 | 0.3922 |
0.0698 | 7.02 | 2800 | 0.3999 |
0.0549 | 8.02 | 3200 | 0.4077 |
0.0477 | 9.02 | 3600 | 0.4121 |
Framework versions
- PEFT 0.11.2.dev0
- Transformers 4.36.0
- Pytorch 2.1.0
- Datasets 2.15.0
- Tokenizers 0.15.1