--- language: - et license: apache-2.0 base_model: openai/whisper-large-v2 tags: - audio - asr - automatic-speech-recognition - hf-asr-leaderboard model-index: - name: salmon-whisper-large-smj-lr7e-5-test1 results: [] --- # salmon-whisper-large-smj-lr7e-5-test1 This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the NbAiLab/salmon-asr-smj dataset. It achieves the following results on the evaluation set: - step: 999 - validation_loss: 0.9447 - train_loss: 0.3067 - validation_wer: 21.6755 - validation_cer: 5.6661 - validation_exact_wer: 25.0 - validation_exact_cer: 6.1940 ## 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: 7e-05 - lr_scheduler_type: linear - per_device_train_batch_size: 6 - total_train_batch_size_per_node: 48 - total_train_batch_size: 48 - total_optimization_steps: 1,000 - starting_optimization_step: None - finishing_optimization_step: 1,000 - num_train_dataset_workers: 32 - num_hosts: 1 - total_num_training_examples: 48,000 - steps_per_epoch: 385 - num_beams: None - weight_decay: 0.01 - adam_beta1: 0.9 - adam_beta2: 0.98 - adam_epsilon: 1e-06 - dropout: True - bpe_dropout_probability: 0.2 - activation_dropout_probability: 0.1 ### Training results | step | validation_loss | train_loss | validation_wer | validation_cer | validation_exact_wer | validation_exact_cer | |:----:|:---------------:|:----------:|:--------------:|:--------------:|:--------------------:|:--------------------:| | 0 | 4.2254 | 4.6455 | 112.7660 | 59.8700 | 108.1117 | 62.0594 | | 100 | 1.4819 | 0.9353 | 59.0426 | 16.0032 | 61.8351 | 16.8293 | | 200 | 1.2494 | 0.8903 | 43.2181 | 10.9667 | 45.8777 | 11.6311 | | 300 | 1.1444 | 0.8144 | 32.4468 | 8.4281 | 35.6383 | 8.8429 | | 400 | 1.0442 | 1.3240 | 30.1862 | 7.7173 | 33.3777 | 8.2454 | | 500 | 0.9681 | 0.2736 | 25.5319 | 6.3769 | 28.4574 | 6.8711 | | 600 | 1.0579 | 0.4364 | 25.0 | 6.3363 | 28.3245 | 6.8313 | | 700 | 0.9322 | 0.6873 | 23.4043 | 5.9708 | 26.3298 | 6.3732 | | 800 | 0.9255 | 0.3675 | 23.2713 | 6.0114 | 26.5957 | 6.5326 | | 900 | 0.9581 | 0.6156 | 22.4734 | 5.8692 | 26.0638 | 6.4330 | | 999 | 0.9447 | 0.3067 | 21.6755 | 5.6661 | 25.0 | 6.1940 | ### Framework versions - Transformers 4.34.1 - Datasets 2.15.0 - Tokenizers 0.14.0