--- license: apache-2.0 tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-small-sp results: [] --- # whisper-small-sp This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4485 - Wer: 20.6842 ## 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: 0.0005 - 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: 25000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:-------:| | 2.2671 | 0.13 | 1000 | 2.2108 | 76.2667 | | 1.4465 | 0.26 | 2000 | 1.6057 | 67.8753 | | 1.0997 | 0.39 | 3000 | 1.1928 | 54.2433 | | 0.9389 | 0.52 | 4000 | 1.0020 | 47.8307 | | 0.7881 | 0.65 | 5000 | 0.8933 | 46.0046 | | 0.7596 | 0.78 | 6000 | 0.7721 | 38.5595 | | 0.5678 | 0.91 | 7000 | 0.6903 | 36.2897 | | 0.4412 | 1.04 | 8000 | 0.6476 | 32.7473 | | 0.4239 | 1.17 | 9000 | 0.5973 | 30.8142 | | 0.3935 | 1.3 | 10000 | 0.5444 | 29.0208 | | 0.3307 | 1.43 | 11000 | 0.5024 | 27.0434 | | 0.2937 | 1.56 | 12000 | 0.4608 | 24.7318 | | 0.2471 | 1.69 | 13000 | 0.4259 | 22.8940 | | 0.2357 | 1.82 | 14000 | 0.3936 | 21.6018 | | 0.2292 | 1.95 | 15000 | 0.3776 | 20.8004 | | 0.1493 | 2.08 | 16000 | 0.4599 | 24.0491 | | 0.1708 | 2.21 | 17000 | 0.4370 | 23.3443 | | 0.1385 | 2.34 | 18000 | 0.4277 | 22.3171 | | 0.1288 | 2.47 | 19000 | 0.4050 | 21.0118 | | 0.1627 | 2.6 | 20000 | 0.4507 | 23.4004 | | 0.1675 | 2.73 | 21000 | 0.4346 | 22.8261 | | 0.159 | 2.86 | 22000 | 0.4179 | 22.2949 | | 0.1458 | 2.99 | 23000 | 0.3978 | 21.0810 | | 0.0487 | 3.12 | 24000 | 0.4456 | 20.8617 | | 0.0401 | 3.25 | 25000 | 0.4485 | 20.6842 | ### Framework versions - Transformers 4.25.1 - Pytorch 1.13.0+cu117 - Datasets 2.7.1 - Tokenizers 0.13.2