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--- |
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library_name: transformers |
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language: |
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- xh |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b-all |
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tags: |
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- generated_from_trainer |
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datasets: |
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- NCHLT_speech_corpus |
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metrics: |
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- wer |
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model-index: |
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- name: facebook mms-1b-all xhosa - Beijuka Bruno |
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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: NCHLT_speech_corpus/Xhosa |
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type: NCHLT_speech_corpus |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.32969196868113837 |
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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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# facebook mms-1b-all xhosa - Beijuka Bruno |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the NCHLT_speech_corpus/Xhosa dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2280 |
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- Model Preparation Time: 0.0199 |
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- Wer: 0.3297 |
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- Cer: 0.0622 |
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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: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- optimizer: Use adamw_torch 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_steps: 100 |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:----------------------:|:------:|:------:| |
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| 161.2211 | 0.9888 | 33 | 16.9451 | 0.0199 | 4.5936 | 1.5848 | |
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| 67.6701 | 1.9888 | 66 | 3.0671 | 0.0199 | 1.0 | 0.8589 | |
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| 14.5117 | 2.9888 | 99 | 0.4740 | 0.0199 | 0.5122 | 0.0912 | |
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| 4.1033 | 3.9888 | 132 | 0.2786 | 0.0199 | 0.3982 | 0.0621 | |
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| 3.1614 | 4.9888 | 165 | 0.2421 | 0.0199 | 0.3497 | 0.0555 | |
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| 2.9473 | 5.9888 | 198 | 0.2270 | 0.0199 | 0.3260 | 0.0517 | |
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| 2.7283 | 6.9888 | 231 | 0.2164 | 0.0199 | 0.3242 | 0.05 | |
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| 2.5382 | 7.9888 | 264 | 0.2095 | 0.0199 | 0.3012 | 0.0475 | |
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| 2.4532 | 8.9888 | 297 | 0.2051 | 0.0199 | 0.3016 | 0.0479 | |
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| 2.3352 | 9.9888 | 330 | 0.1977 | 0.0199 | 0.3037 | 0.0465 | |
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| 2.2913 | 10.9888 | 363 | 0.1966 | 0.0199 | 0.2906 | 0.0460 | |
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| 2.2131 | 11.9888 | 396 | 0.1998 | 0.0199 | 0.3101 | 0.0464 | |
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| 2.1296 | 12.9888 | 429 | 0.1912 | 0.0199 | 0.2821 | 0.0444 | |
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| 2.0863 | 13.9888 | 462 | 0.1934 | 0.0199 | 0.2796 | 0.0442 | |
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| 2.016 | 14.9888 | 495 | 0.1927 | 0.0199 | 0.2761 | 0.0439 | |
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| 1.9625 | 15.9888 | 528 | 0.1896 | 0.0199 | 0.2758 | 0.0438 | |
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| 1.9719 | 16.9888 | 561 | 0.1921 | 0.0199 | 0.2581 | 0.0422 | |
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| 1.8811 | 17.9888 | 594 | 0.1910 | 0.0199 | 0.2736 | 0.0435 | |
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| 1.759 | 18.9888 | 627 | 0.1913 | 0.0199 | 0.2680 | 0.0433 | |
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| 1.7474 | 19.9888 | 660 | 0.1883 | 0.0199 | 0.2602 | 0.0426 | |
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| 1.6931 | 20.9888 | 693 | 0.1925 | 0.0199 | 0.2669 | 0.0430 | |
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| 1.6515 | 21.9888 | 726 | 0.1879 | 0.0199 | 0.2591 | 0.0423 | |
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| 1.6038 | 22.9888 | 759 | 0.1919 | 0.0199 | 0.2676 | 0.0431 | |
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| 1.608 | 23.9888 | 792 | 0.1960 | 0.0199 | 0.2665 | 0.0426 | |
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| 1.6418 | 24.9888 | 825 | 0.1940 | 0.0199 | 0.2612 | 0.0418 | |
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| 1.5068 | 25.9888 | 858 | 0.1985 | 0.0199 | 0.2609 | 0.0427 | |
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| 1.5171 | 26.9888 | 891 | 0.1932 | 0.0199 | 0.2612 | 0.0423 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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