--- language: - nl license: apache-2.0 base_model: openai/whisper-large-v2 tags: - generated_from_trainer metrics: - wer model-index: - name: Whisper Large V2 results: [] --- # Whisper Large V2 This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1460 - Wer: 4.9428 ## 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: 3e-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: 20 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.4482 | 0.38 | 30 | 0.2117 | 7.6578 | | 0.1832 | 0.75 | 60 | 0.1544 | 6.4124 | | 0.1302 | 1.12 | 90 | 0.1546 | 6.0953 | | 0.0785 | 1.5 | 120 | 0.1436 | 6.8765 | | 0.0777 | 1.88 | 150 | 0.1350 | 5.3914 | | 0.0546 | 2.25 | 180 | 0.1431 | 5.4069 | | 0.0311 | 2.62 | 210 | 0.1411 | 9.5452 | | 0.0334 | 3.0 | 240 | 0.1389 | 6.0334 | | 0.0172 | 3.38 | 270 | 0.1404 | 5.1361 | | 0.0147 | 3.75 | 300 | 0.1414 | 5.2754 | | 0.0108 | 4.12 | 330 | 0.1420 | 5.0588 | | 0.0073 | 4.5 | 360 | 0.1454 | 4.9273 | | 0.007 | 4.88 | 390 | 0.1460 | 4.9428 | ### Framework versions - Transformers 4.38.0.dev0 - Pytorch 2.1.0+cu121 - Datasets 2.14.6 - Tokenizers 0.15.0