metadata
language:
- hi
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hi - Swedish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
split: None
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 19.647226479524615
Whisper Small Hi - Swedish
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3953
- Wer: 19.6472
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: 8
- 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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1331 | 1.29 | 1000 | 0.3014 | 22.3602 |
| 0.0537 | 2.59 | 2000 | 0.2988 | 20.8572 |
| 0.0217 | 3.88 | 3000 | 0.3093 | 20.5641 |
| 0.004 | 5.17 | 4000 | 0.3551 | 20.0479 |
| 0.0015 | 6.47 | 5000 | 0.3701 | 20.0022 |
| 0.0015 | 7.76 | 6000 | 0.3769 | 19.7386 |
| 0.0007 | 9.06 | 7000 | 0.3908 | 19.7010 |
| 0.0006 | 10.35 | 8000 | 0.3953 | 19.6472 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.9.0+cu102
- Datasets 2.7.1
- Tokenizers 0.13.2