metadata
language:
- sv
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: whisper-small-test
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0
type: mozilla-foundation/common_voice_13_0
config: default
split: test
args: 'config: sv, split: test'
metrics:
- name: Wer
type: wer
value: 30.900127226463102
whisper-small-test
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4846
- Wer: 30.9001
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 6000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5133 | 0.64 | 500 | 0.5562 | 38.3826 |
| 0.3764 | 1.28 | 1000 | 0.4754 | 34.1921 |
| 0.3501 | 1.92 | 1500 | 0.4554 | 32.8509 |
| 0.222 | 2.55 | 2000 | 0.4399 | 32.3844 |
| 0.1283 | 3.19 | 2500 | 0.4440 | 32.0081 |
| 0.1575 | 3.83 | 3000 | 0.4295 | 31.8225 |
| 0.1205 | 4.47 | 3500 | 0.4410 | 31.0459 |
| 0.0992 | 5.11 | 4000 | 0.4505 | 31.1042 |
| 0.0941 | 5.75 | 4500 | 0.4551 | 30.8498 |
| 0.0627 | 6.39 | 5000 | 0.4696 | 31.5999 |
| 0.0652 | 7.02 | 5500 | 0.4761 | 31.8013 |
| 0.0573 | 7.66 | 6000 | 0.4846 | 30.9001 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0