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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-small-CV_Fleurs_AMMI_ALFFA-sw-10hrs-v1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# whisper-small-CV_Fleurs_AMMI_ALFFA-sw-10hrs-v1 |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9490 |
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- Wer: 0.2851 |
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- Cer: 0.1098 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 100 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:| |
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| 3.7806 | 0.9986 | 360 | 0.8995 | 0.6431 | 0.2391 | |
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| 1.3216 | 2.0 | 721 | 0.6455 | 0.4377 | 0.1689 | |
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| 0.7711 | 2.9986 | 1081 | 0.5796 | 0.4257 | 0.1831 | |
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| 0.439 | 4.0 | 1442 | 0.5872 | 0.4005 | 0.1697 | |
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| 0.275 | 4.9986 | 1802 | 0.5826 | 0.3129 | 0.1115 | |
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| 0.2006 | 6.0 | 2163 | 0.6350 | 0.3191 | 0.1166 | |
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| 0.1783 | 6.9986 | 2523 | 0.6342 | 0.3165 | 0.1108 | |
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| 0.1629 | 8.0 | 2884 | 0.6669 | 0.3099 | 0.1127 | |
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| 0.1564 | 8.9986 | 3244 | 0.6764 | 0.3390 | 0.1387 | |
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| 0.1575 | 10.0 | 3605 | 0.7052 | 0.3367 | 0.1351 | |
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| 0.1524 | 10.9986 | 3965 | 0.7088 | 0.3116 | 0.1149 | |
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| 0.128 | 12.0 | 4326 | 0.7365 | 0.3661 | 0.1603 | |
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| 0.1148 | 12.9986 | 4686 | 0.7283 | 0.3089 | 0.1132 | |
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| 0.0946 | 14.0 | 5047 | 0.7364 | 0.3046 | 0.1118 | |
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| 0.0826 | 14.9986 | 5407 | 0.7805 | 0.2963 | 0.1105 | |
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| 0.0751 | 16.0 | 5768 | 0.7608 | 0.3273 | 0.1291 | |
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| 0.0697 | 16.9986 | 6128 | 0.7748 | 0.2941 | 0.1089 | |
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| 0.0659 | 18.0 | 6489 | 0.7887 | 0.3064 | 0.1142 | |
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| 0.0547 | 18.9986 | 6849 | 0.7944 | 0.2943 | 0.1124 | |
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| 0.0531 | 20.0 | 7210 | 0.8065 | 0.2921 | 0.1094 | |
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| 0.0495 | 20.9986 | 7570 | 0.7981 | 0.2897 | 0.1056 | |
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| 0.0481 | 22.0 | 7931 | 0.8201 | 0.2927 | 0.1089 | |
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| 0.0437 | 22.9986 | 8291 | 0.8175 | 0.2958 | 0.1126 | |
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| 0.0392 | 24.0 | 8652 | 0.8470 | 0.3106 | 0.1214 | |
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| 0.0379 | 24.9986 | 9012 | 0.8203 | 0.2965 | 0.1143 | |
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| 0.0332 | 26.0 | 9373 | 0.8315 | 0.2848 | 0.1062 | |
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| 0.0335 | 26.9986 | 9733 | 0.8485 | 0.2857 | 0.1040 | |
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| 0.0296 | 28.0 | 10094 | 0.8591 | 0.2997 | 0.1154 | |
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| 0.0267 | 28.9986 | 10454 | 0.8672 | 0.2910 | 0.1084 | |
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| 0.0291 | 30.0 | 10815 | 0.8552 | 0.2905 | 0.1069 | |
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| 0.0275 | 30.9986 | 11175 | 0.8441 | 0.2901 | 0.1081 | |
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| 0.0248 | 32.0 | 11536 | 0.8693 | 0.2897 | 0.1107 | |
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| 0.0233 | 32.9986 | 11896 | 0.8582 | 0.2830 | 0.1037 | |
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| 0.0208 | 34.0 | 12257 | 0.8740 | 0.2911 | 0.1112 | |
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| 0.0186 | 34.9986 | 12617 | 0.8843 | 0.2832 | 0.1061 | |
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| 0.0187 | 36.0 | 12978 | 0.8962 | 0.2877 | 0.1056 | |
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| 0.0186 | 36.9986 | 13338 | 0.9004 | 0.2855 | 0.1069 | |
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| 0.0174 | 38.0 | 13699 | 0.8975 | 0.2829 | 0.1059 | |
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| 0.0151 | 38.9986 | 14059 | 0.8970 | 0.2879 | 0.1081 | |
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| 0.0146 | 40.0 | 14420 | 0.9029 | 0.2877 | 0.1075 | |
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| 0.014 | 40.9986 | 14780 | 0.9081 | 0.2815 | 0.1038 | |
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| 0.0155 | 42.0 | 15141 | 0.8880 | 0.2774 | 0.1057 | |
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| 0.0138 | 42.9986 | 15501 | 0.9054 | 0.2810 | 0.1048 | |
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| 0.0136 | 44.0 | 15862 | 0.9054 | 0.2807 | 0.1078 | |
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| 0.013 | 44.9986 | 16222 | 0.9033 | 0.2810 | 0.1066 | |
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| 0.011 | 46.0 | 16583 | 0.9044 | 0.2833 | 0.1097 | |
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| 0.0105 | 46.9986 | 16943 | 0.9064 | 0.2796 | 0.1036 | |
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| 0.0101 | 48.0 | 17304 | 0.9049 | 0.2823 | 0.1058 | |
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| 0.0072 | 48.9986 | 17664 | 0.9250 | 0.2870 | 0.1086 | |
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| 0.0116 | 50.0 | 18025 | 0.9556 | 0.2729 | 0.1001 | |
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| 0.0094 | 50.9986 | 18385 | 0.9187 | 0.2820 | 0.1073 | |
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| 0.0069 | 52.0 | 18746 | 0.9249 | 0.2828 | 0.1092 | |
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| 0.0077 | 52.9986 | 19106 | 0.9443 | 0.2891 | 0.1139 | |
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| 0.0088 | 54.0 | 19467 | 0.9336 | 0.2888 | 0.1127 | |
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| 0.0076 | 54.9986 | 19827 | 0.9416 | 0.2831 | 0.1074 | |
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| 0.0064 | 56.0 | 20188 | 0.9477 | 0.2790 | 0.1058 | |
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| 0.0055 | 56.9986 | 20548 | 0.9273 | 0.2772 | 0.1050 | |
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| 0.005 | 58.0 | 20909 | 0.9315 | 0.2781 | 0.1056 | |
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| 0.0055 | 58.9986 | 21269 | 0.9505 | 0.2855 | 0.1094 | |
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| 0.0064 | 60.0 | 21630 | 0.9490 | 0.2851 | 0.1098 | |
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### Framework versions |
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- Transformers 4.46.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.1 |
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