--- library_name: transformers license: apache-2.0 base_model: openai/whisper-large tags: - generated_from_trainer datasets: - deepinfinityai/30_report_sentences_dataset metrics: - wer model-index: - name: Whisper_Large_30_sent_ModelV2 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: 11 Sentences type: deepinfinityai/30_report_sentences_dataset metrics: - name: Wer type: wer value: 5.0 --- # Whisper_Large_30_sent_ModelV2 This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the 11 Sentences dataset. It achieves the following results on the evaluation set: - Loss: 0.2239 - Wer: 5.0 ## 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: 4 - eval_batch_size: 8 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - training_steps: 500 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-------:|:----:|:---------------:|:----:| | 2.7745 | 8.3333 | 50 | 1.2629 | 40.0 | | 0.0301 | 16.6667 | 100 | 0.1945 | 5.0 | | 0.0 | 25.0 | 150 | 0.2056 | 5.0 | | 0.0 | 33.3333 | 200 | 0.2102 | 5.0 | | 0.0 | 41.6667 | 250 | 0.2140 | 5.0 | | 0.0 | 50.0 | 300 | 0.2172 | 5.0 | | 0.0 | 58.3333 | 350 | 0.2198 | 5.0 | | 0.0 | 66.6667 | 400 | 0.2220 | 5.0 | | 0.0 | 75.0 | 450 | 0.2234 | 5.0 | | 0.0 | 83.3333 | 500 | 0.2239 | 5.0 | ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0