--- base_model: openai/whisper-tiny library_name: transformers license: apache-2.0 metrics: - wer tags: - generated_from_trainer model-index: - name: whisper-tiny-1000-diverse-audios results: [] --- # whisper-tiny-1000-diverse-audios This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1835 - Wer: 42.9577 ## 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: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 25 - training_steps: 500 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:--------:| | 3.7684 | 0.4425 | 25 | 2.2485 | 135.5131 | | 1.5347 | 0.8850 | 50 | 0.9286 | 75.5533 | | 0.8425 | 1.3274 | 75 | 0.5561 | 56.4386 | | 0.5722 | 1.7699 | 100 | 0.4103 | 43.4608 | | 0.3867 | 2.2124 | 125 | 0.3423 | 40.5433 | | 0.3107 | 2.6549 | 150 | 0.2967 | 51.0060 | | 0.2931 | 3.0973 | 175 | 0.2656 | 78.8732 | | 0.2031 | 3.5398 | 200 | 0.2421 | 57.8471 | | 0.2004 | 3.9823 | 225 | 0.2305 | 51.8109 | | 0.1254 | 4.4248 | 250 | 0.2198 | 22.4346 | | 0.1332 | 4.8673 | 275 | 0.2070 | 22.2334 | | 0.1089 | 5.3097 | 300 | 0.2049 | 51.4085 | | 0.0627 | 5.7522 | 325 | 0.1988 | 28.5714 | | 0.0959 | 6.1947 | 350 | 0.1948 | 31.6901 | | 0.0794 | 6.6372 | 375 | 0.1910 | 28.8732 | | 0.0696 | 7.0796 | 400 | 0.1879 | 43.5614 | | 0.0458 | 7.5221 | 425 | 0.1861 | 43.4608 | | 0.0524 | 7.9646 | 450 | 0.1841 | 53.5211 | | 0.0453 | 8.4071 | 475 | 0.1832 | 40.4427 | | 0.0485 | 8.8496 | 500 | 0.1835 | 42.9577 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cu121 - Datasets 3.0.0 - Tokenizers 0.19.1