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--- |
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license: apache-2.0 |
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base_model: Akashpb13/Swahili_xlsr |
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tags: |
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- generated_from_trainer |
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datasets: |
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- ml-superb-subset |
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metrics: |
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- wer |
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model-index: |
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- name: xho_finetune |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: ml-superb-subset |
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type: ml-superb-subset |
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config: xho |
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split: test |
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args: xho |
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metrics: |
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- name: Wer |
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type: wer |
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value: 53.510895883777245 |
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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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# xho_finetune |
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This model is a fine-tuned version of [Akashpb13/Swahili_xlsr](https://huggingface.co/Akashpb13/Swahili_xlsr) on the ml-superb-subset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5370 |
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- Wer: 53.5109 |
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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: 9.6e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 25 |
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- training_steps: 500 |
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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 | |
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|:-------------:|:-------:|:----:|:---------------:|:-------:| |
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| 25.5184 | 0.7692 | 10 | 24.2275 | 100.0 | |
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| 14.5363 | 1.5385 | 20 | 9.8357 | 100.0 | |
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| 4.5811 | 2.3077 | 30 | 3.8367 | 100.0 | |
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| 3.4822 | 3.0769 | 40 | 3.3922 | 100.0 | |
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| 3.2732 | 3.8462 | 50 | 3.2398 | 100.0 | |
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| 3.1796 | 4.6154 | 60 | 3.1705 | 100.0 | |
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| 3.1504 | 5.3846 | 70 | 3.1419 | 100.0 | |
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| 3.1119 | 6.1538 | 80 | 3.1084 | 100.0 | |
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| 3.0789 | 6.9231 | 90 | 3.0735 | 100.0 | |
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| 3.0619 | 7.6923 | 100 | 3.0590 | 100.0 | |
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| 3.0298 | 8.4615 | 110 | 3.0247 | 100.0 | |
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| 2.9933 | 9.2308 | 120 | 2.9716 | 100.0 | |
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| 2.9079 | 10.0 | 130 | 2.8647 | 100.0 | |
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| 2.8414 | 10.7692 | 140 | 2.7931 | 100.0 | |
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| 2.6939 | 11.5385 | 150 | 2.5932 | 100.0 | |
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| 2.3274 | 12.3077 | 160 | 2.1000 | 99.7579 | |
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| 1.7068 | 13.0769 | 170 | 1.4580 | 93.4625 | |
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| 1.206 | 13.8462 | 180 | 1.1027 | 83.0508 | |
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| 0.9587 | 14.6154 | 190 | 0.9152 | 79.4189 | |
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| 0.7806 | 15.3846 | 200 | 0.8122 | 69.7337 | |
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| 0.7118 | 16.1538 | 210 | 0.7445 | 69.0073 | |
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| 0.6814 | 16.9231 | 220 | 0.6945 | 62.9540 | |
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| 0.5709 | 17.6923 | 230 | 0.6787 | 67.5545 | |
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| 0.5653 | 18.4615 | 240 | 0.6758 | 62.2276 | |
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| 0.5437 | 19.2308 | 250 | 0.6511 | 60.7748 | |
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| 0.5092 | 20.0 | 260 | 0.6237 | 62.7119 | |
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| 0.4239 | 20.7692 | 270 | 0.6000 | 61.5012 | |
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| 0.4355 | 21.5385 | 280 | 0.5899 | 59.8063 | |
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| 0.4456 | 22.3077 | 290 | 0.5960 | 59.3220 | |
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| 0.3986 | 23.0769 | 300 | 0.5764 | 56.6586 | |
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| 0.3856 | 23.8462 | 310 | 0.5801 | 55.9322 | |
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| 0.3607 | 24.6154 | 320 | 0.5682 | 57.6271 | |
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| 0.358 | 25.3846 | 330 | 0.5675 | 55.9322 | |
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| 0.3452 | 26.1538 | 340 | 0.5630 | 57.8692 | |
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| 0.3289 | 26.9231 | 350 | 0.5515 | 57.8692 | |
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| 0.353 | 27.6923 | 360 | 0.5621 | 57.3850 | |
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| 0.2907 | 28.4615 | 370 | 0.5486 | 55.2058 | |
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| 0.3237 | 29.2308 | 380 | 0.5445 | 54.4794 | |
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| 0.3202 | 30.0 | 390 | 0.5384 | 52.7845 | |
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| 0.2918 | 30.7692 | 400 | 0.5370 | 55.6901 | |
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| 0.3106 | 31.5385 | 410 | 0.5422 | 53.7530 | |
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| 0.3105 | 32.3077 | 420 | 0.5438 | 55.2058 | |
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| 0.2835 | 33.0769 | 430 | 0.5437 | 55.9322 | |
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| 0.2966 | 33.8462 | 440 | 0.5416 | 54.7215 | |
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| 0.2719 | 34.6154 | 450 | 0.5394 | 54.2373 | |
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| 0.2859 | 35.3846 | 460 | 0.5384 | 53.7530 | |
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| 0.29 | 36.1538 | 470 | 0.5379 | 53.2688 | |
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| 0.2879 | 36.9231 | 480 | 0.5372 | 53.5109 | |
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| 0.2871 | 37.6923 | 490 | 0.5370 | 53.5109 | |
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| 0.3019 | 38.4615 | 500 | 0.5370 | 53.5109 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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