metadata
language:
- lt
license: apache-2.0
tags:
- lt-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small LT - Lithuanian Whisper
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: train+validation
args: lt
metrics:
- name: Wer
type: wer
value: 32.65614439629468
Whisper Small LT - Lithuanian Whisper
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: 0.3871
- Wer: 32.6561
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: 4000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.2419 | 1.8 | 1000 | 0.3749 | 38.7707 |
0.0425 | 3.6 | 2000 | 0.3591 | 34.2345 |
0.0062 | 5.4 | 3000 | 0.3779 | 32.7555 |
0.0034 | 7.19 | 4000 | 0.3871 | 32.6561 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2