--- 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](WHISPER.png) # Whisper Small LT - Lithuanian Whisper This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/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