metadata
language:
- lt
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Lt
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: lt
split: test
args: lt
metrics:
- name: Wer
type: wer
value: 35.859768928415455
Whisper Small Lt
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: 0.5724
- Wer: 35.8598
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: 32
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0237 | 6.0 | 1000 | 0.4745 | 37.9839 |
| 0.0016 | 12.01 | 2000 | 0.5128 | 35.9749 |
| 0.0008 | 18.01 | 3000 | 0.5458 | 35.7843 |
| 0.0005 | 24.02 | 4000 | 0.5652 | 35.8240 |
| 0.0004 | 30.02 | 5000 | 0.5724 | 35.8598 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2