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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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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: amh_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: amh |
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split: test |
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args: amh |
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metrics: |
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- name: Wer |
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type: wer |
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value: 97.41641337386018 |
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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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# amh_finetune |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the ml-superb-subset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8917 |
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- Wer: 97.4164 |
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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: 0.001 |
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- train_batch_size: 64 |
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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: 128 |
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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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| 22.5796 | 2.2222 | 10 | 17.1583 | 100.0 | |
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| 9.5568 | 4.4444 | 20 | 7.4797 | 100.0 | |
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| 4.3875 | 6.6667 | 30 | 3.9841 | 100.0 | |
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| 3.8631 | 8.8889 | 40 | 3.8281 | 100.0 | |
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| 3.8298 | 11.1111 | 50 | 3.8117 | 100.0 | |
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| 3.7925 | 13.3333 | 60 | 3.7866 | 100.0 | |
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| 3.802 | 15.5556 | 70 | 3.7763 | 100.0 | |
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| 3.7845 | 17.7778 | 80 | 3.7681 | 100.0 | |
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| 3.7732 | 20.0 | 90 | 3.7627 | 100.0 | |
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| 3.7547 | 22.2222 | 100 | 3.7625 | 100.0 | |
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| 3.7471 | 24.4444 | 110 | 3.7588 | 100.0 | |
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| 3.7378 | 26.6667 | 120 | 3.7244 | 100.0 | |
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| 3.7278 | 28.8889 | 130 | 3.7337 | 100.0 | |
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| 3.71 | 31.1111 | 140 | 3.7188 | 100.0 | |
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| 3.6966 | 33.3333 | 150 | 3.7076 | 100.0 | |
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| 3.6811 | 35.5556 | 160 | 3.6916 | 100.0 | |
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| 3.6741 | 37.7778 | 170 | 3.6898 | 100.0 | |
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| 3.6337 | 40.0 | 180 | 3.6486 | 100.0 | |
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| 3.5766 | 42.2222 | 190 | 3.5913 | 100.0 | |
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| 3.5251 | 44.4444 | 200 | 3.5318 | 100.0 | |
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| 3.4533 | 46.6667 | 210 | 3.4549 | 100.0 | |
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| 3.3664 | 48.8889 | 220 | 3.3877 | 100.0 | |
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| 3.2963 | 51.1111 | 230 | 3.2852 | 100.0 | |
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| 3.1237 | 53.3333 | 240 | 3.1187 | 100.0 | |
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| 2.9356 | 55.5556 | 250 | 2.9620 | 100.0 | |
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| 2.7107 | 57.7778 | 260 | 2.7665 | 100.0 | |
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| 2.477 | 60.0 | 270 | 2.5155 | 99.3921 | |
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| 2.1786 | 62.2222 | 280 | 2.2953 | 98.4043 | |
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| 1.897 | 64.4444 | 290 | 2.1781 | 97.5684 | |
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| 1.6863 | 66.6667 | 300 | 2.1825 | 97.5684 | |
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| 1.4954 | 68.8889 | 310 | 2.1240 | 96.2766 | |
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| 1.3132 | 71.1111 | 320 | 2.1476 | 94.3769 | |
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| 1.1333 | 73.3333 | 330 | 2.2088 | 95.6687 | |
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| 0.9827 | 75.5556 | 340 | 2.2591 | 94.9088 | |
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| 0.9019 | 77.7778 | 350 | 2.4481 | 101.0638 | |
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| 0.7936 | 80.0 | 360 | 2.5467 | 103.4195 | |
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| 0.7015 | 82.2222 | 370 | 2.5279 | 95.5927 | |
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| 0.631 | 84.4444 | 380 | 2.6338 | 95.8207 | |
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| 0.5849 | 86.6667 | 390 | 2.6840 | 96.8085 | |
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| 0.5549 | 88.8889 | 400 | 2.7048 | 97.4164 | |
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| 0.5137 | 91.1111 | 410 | 2.7910 | 96.0486 | |
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| 0.4905 | 93.3333 | 420 | 2.8070 | 98.7842 | |
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| 0.4603 | 95.5556 | 430 | 2.8552 | 95.2888 | |
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| 0.457 | 97.7778 | 440 | 2.8382 | 95.8207 | |
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| 0.442 | 100.0 | 450 | 2.8831 | 98.2523 | |
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| 0.4437 | 102.2222 | 460 | 2.8800 | 97.5684 | |
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| 0.4346 | 104.4444 | 470 | 2.8805 | 97.7964 | |
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| 0.4341 | 106.6667 | 480 | 2.8864 | 97.6444 | |
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| 0.4319 | 108.8889 | 490 | 2.8911 | 97.3404 | |
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| 0.4403 | 111.1111 | 500 | 2.8917 | 97.4164 | |
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### Framework versions |
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- Transformers 4.41.0 |
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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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