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--- |
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language: |
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- all |
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license: apache-2.0 |
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tags: |
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- minds14 |
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- google/xtreme_s |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: xtreme_s_xlsr_t5lephone-small_minds14.en-all |
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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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# xtreme_s_xlsr_t5lephone-small_minds14.en-all |
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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 GOOGLE/XTREME_S - MINDS14.ALL dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5979 |
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- F1: 0.8918 |
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- Accuracy: 0.8921 |
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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: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 1500 |
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- num_epochs: 150.0 |
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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 | F1 | Accuracy | |
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|:-------------:|:------:|:-----:|:---------------:|:------:|:--------:| |
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| 2.3561 | 2.98 | 200 | 2.5464 | 0.0681 | 0.1334 | |
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| 1.1851 | 5.97 | 400 | 1.5056 | 0.5583 | 0.5861 | |
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| 1.2805 | 8.95 | 600 | 1.1397 | 0.7106 | 0.7044 | |
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| 1.0801 | 11.94 | 800 | 0.9863 | 0.7132 | 0.7198 | |
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| 0.9285 | 14.92 | 1000 | 0.9912 | 0.7037 | 0.7139 | |
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| 0.4164 | 17.91 | 1200 | 0.8226 | 0.7743 | 0.7741 | |
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| 0.7669 | 20.89 | 1400 | 0.8131 | 0.7783 | 0.7788 | |
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| 0.4606 | 23.88 | 1600 | 0.8314 | 0.7879 | 0.7792 | |
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| 0.6975 | 26.86 | 1800 | 0.7667 | 0.7927 | 0.7939 | |
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| 0.9913 | 29.85 | 2000 | 0.9207 | 0.7734 | 0.7707 | |
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| 0.2307 | 32.83 | 2200 | 0.7651 | 0.8072 | 0.8086 | |
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| 0.1412 | 35.82 | 2400 | 0.7132 | 0.8352 | 0.8311 | |
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| 0.2141 | 38.8 | 2600 | 0.7551 | 0.8276 | 0.8262 | |
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| 0.2169 | 41.79 | 2800 | 0.7900 | 0.8148 | 0.8160 | |
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| 0.3942 | 44.77 | 3000 | 0.8621 | 0.8130 | 0.8042 | |
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| 0.2306 | 47.76 | 3200 | 0.6788 | 0.8264 | 0.8253 | |
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| 0.0975 | 50.74 | 3400 | 0.7236 | 0.8295 | 0.8289 | |
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| 0.0062 | 53.73 | 3600 | 0.6872 | 0.8286 | 0.8277 | |
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| 0.1781 | 56.71 | 3800 | 0.6990 | 0.8393 | 0.8390 | |
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| 0.0309 | 59.7 | 4000 | 0.6348 | 0.8496 | 0.8500 | |
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| 0.0026 | 62.68 | 4200 | 0.6737 | 0.8585 | 0.8566 | |
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| 0.0043 | 65.67 | 4400 | 0.7780 | 0.8416 | 0.8387 | |
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| 0.0032 | 68.65 | 4600 | 0.6899 | 0.8482 | 0.8461 | |
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| 0.0302 | 71.64 | 4800 | 0.6813 | 0.8515 | 0.8495 | |
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| 0.0027 | 74.62 | 5000 | 0.7163 | 0.8530 | 0.8529 | |
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| 0.1165 | 77.61 | 5200 | 0.6249 | 0.8603 | 0.8595 | |
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| 0.0021 | 80.59 | 5400 | 0.6747 | 0.8588 | 0.8578 | |
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| 0.2558 | 83.58 | 5600 | 0.7514 | 0.8581 | 0.8581 | |
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| 0.0162 | 86.57 | 5800 | 0.6782 | 0.8667 | 0.8664 | |
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| 0.1929 | 89.55 | 6000 | 0.6371 | 0.8615 | 0.8600 | |
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| 0.0621 | 92.54 | 6200 | 0.8079 | 0.8600 | 0.8607 | |
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| 0.0017 | 95.52 | 6400 | 0.7072 | 0.8678 | 0.8669 | |
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| 0.0008 | 98.51 | 6600 | 0.7323 | 0.8572 | 0.8541 | |
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| 0.1655 | 101.49 | 6800 | 0.6953 | 0.8521 | 0.8505 | |
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| 0.01 | 104.48 | 7000 | 0.7149 | 0.8665 | 0.8674 | |
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| 0.0135 | 107.46 | 7200 | 0.8990 | 0.8523 | 0.8488 | |
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| 0.0056 | 110.45 | 7400 | 0.7320 | 0.8673 | 0.8664 | |
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| 0.0023 | 113.43 | 7600 | 0.7108 | 0.8700 | 0.8705 | |
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| 0.0025 | 116.42 | 7800 | 0.6464 | 0.8818 | 0.8820 | |
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| 0.0003 | 119.4 | 8000 | 0.6985 | 0.8706 | 0.8713 | |
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| 0.0048 | 122.39 | 8200 | 0.6620 | 0.8765 | 0.8740 | |
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| 0.2335 | 125.37 | 8400 | 0.6515 | 0.8832 | 0.8828 | |
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| 0.0005 | 128.36 | 8600 | 0.6961 | 0.8776 | 0.8762 | |
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| 0.0003 | 131.34 | 8800 | 0.5990 | 0.8878 | 0.8882 | |
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| 0.0002 | 134.33 | 9000 | 0.6236 | 0.8887 | 0.8889 | |
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| 0.002 | 137.31 | 9200 | 0.6671 | 0.8847 | 0.8845 | |
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| 0.0002 | 140.3 | 9400 | 0.5970 | 0.8931 | 0.8935 | |
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| 0.0002 | 143.28 | 9600 | 0.6095 | 0.8906 | 0.8913 | |
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| 0.0002 | 146.27 | 9800 | 0.6056 | 0.8910 | 0.8913 | |
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| 0.0002 | 149.25 | 10000 | 0.5979 | 0.8918 | 0.8921 | |
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### Framework versions |
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- Transformers 4.20.0.dev0 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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