--- license: apache-2.0 tags: - generated_from_trainer base_model: openai/whisper-small datasets: - mozilla-foundation/fsc-audio-dataset metrics: - wer model-index: - name: Personalized Whisper Small - Wei Fang results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: fsc-audio-dataset type: mozilla-foundation/fsc-audio-dataset metrics: - type: wer value: 8.372290692732681 name: Wer --- # Personalized Whisper Small - Wei Fang This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the fsc-audio-dataset dataset. It achieves the following results on the evaluation set: - Loss: 0.2946 - Wer: 8.3723 ## 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: 32 - 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: 4000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.9814 | 0.32 | 100 | 0.8164 | 13.2172 | | 0.3013 | 0.64 | 200 | 0.2578 | 11.7722 | | 0.2074 | 0.96 | 300 | 0.2192 | 10.4972 | | 0.1429 | 1.28 | 400 | 0.2245 | 11.0072 | | 0.1565 | 1.6 | 500 | 0.2102 | 10.6247 | | 0.1554 | 1.92 | 600 | 0.2137 | 11.2197 | | 0.0684 | 2.24 | 700 | 0.2139 | 8.8823 | | 0.0717 | 2.56 | 800 | 0.2142 | 9.6898 | | 0.0795 | 2.88 | 900 | 0.2128 | 9.2223 | | 0.0329 | 3.21 | 1000 | 0.2341 | 9.3073 | | 0.03 | 3.53 | 1100 | 0.2324 | 8.9673 | | 0.0319 | 3.85 | 1200 | 0.2365 | 9.0948 | | 0.0137 | 4.17 | 1300 | 0.2403 | 9.0523 | | 0.0145 | 4.49 | 1400 | 0.2470 | 8.3723 | | 0.0145 | 4.81 | 1500 | 0.2596 | 9.4348 | | 0.0067 | 5.13 | 1600 | 0.2544 | 8.9248 | | 0.0088 | 5.45 | 1700 | 0.2553 | 8.4573 | | 0.0065 | 5.77 | 1800 | 0.2729 | 8.8823 | | 0.0018 | 6.09 | 1900 | 0.2680 | 8.7973 | | 0.0023 | 6.41 | 2000 | 0.2710 | 9.0948 | | 0.0018 | 6.73 | 2100 | 0.2762 | 8.8398 | | 0.002 | 7.05 | 2200 | 0.2717 | 8.5848 | | 0.0011 | 7.37 | 2300 | 0.2784 | 8.5423 | | 0.0012 | 7.69 | 2400 | 0.2797 | 8.4573 | | 0.0011 | 8.01 | 2500 | 0.2782 | 8.3723 | | 0.0007 | 8.33 | 2600 | 0.2838 | 8.1598 | | 0.0007 | 8.65 | 2700 | 0.2826 | 8.2448 | | 0.0013 | 8.97 | 2800 | 0.2835 | 8.4148 | | 0.0006 | 9.29 | 2900 | 0.2913 | 8.2448 | | 0.0006 | 9.62 | 3000 | 0.2906 | 8.4148 | | 0.001 | 9.94 | 3100 | 0.2886 | 8.6273 | | 0.0005 | 10.26 | 3200 | 0.2890 | 8.3723 | | 0.0005 | 10.58 | 3300 | 0.2905 | 8.3723 | | 0.0005 | 10.9 | 3400 | 0.2917 | 8.4573 | | 0.0008 | 11.22 | 3500 | 0.2927 | 8.3723 | | 0.0019 | 11.54 | 3600 | 0.2932 | 8.3723 | | 0.0004 | 11.86 | 3700 | 0.2939 | 8.3723 | | 0.0004 | 12.18 | 3800 | 0.2941 | 8.3723 | | 0.0005 | 12.5 | 3900 | 0.2944 | 8.3723 | | 0.0005 | 12.82 | 4000 | 0.2946 | 8.3723 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2