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--- |
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library_name: transformers |
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language: |
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- sn |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-300m |
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tags: |
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- generated_from_trainer |
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datasets: |
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- DigitalUmuganda_Afrivoice/Shona |
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metrics: |
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- wer |
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model-index: |
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- name: facebook/mms-300m |
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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: DigitalUmuganda |
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type: DigitalUmuganda_Afrivoice/Shona |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.41041838767675787 |
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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-300m |
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This model is a fine-tuned version of [facebook/mms-300m](https://huggingface.co/facebook/mms-300m) on the DigitalUmuganda dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8585 |
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- Wer: 0.4104 |
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- Cer: 0.0907 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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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- 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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| 33.7728 | 0.9955 | 55 | 3.2848 | 1.0 | 1.0 | |
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| 12.0407 | 1.9910 | 110 | 2.9063 | 1.0 | 1.0 | |
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| 11.7013 | 2.9864 | 165 | 2.8895 | 1.0 | 1.0 | |
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| 11.2973 | 4.0 | 221 | 2.8169 | 1.0 | 1.0 | |
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| 11.1719 | 4.9955 | 276 | 2.5708 | 1.0 | 0.8738 | |
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| 8.8604 | 5.9910 | 331 | 1.6831 | 1.0 | 0.5577 | |
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| 6.0356 | 6.9864 | 386 | 1.1403 | 0.9983 | 0.3583 | |
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| 4.3072 | 8.0 | 442 | 0.8494 | 0.9471 | 0.2649 | |
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| 3.3072 | 8.9955 | 497 | 0.6382 | 0.8545 | 0.1923 | |
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| 2.3828 | 9.9910 | 552 | 0.4925 | 0.6959 | 0.1443 | |
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| 1.7086 | 10.9864 | 607 | 0.3803 | 0.5268 | 0.1041 | |
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| 1.2672 | 12.0 | 663 | 0.3669 | 0.4825 | 0.0934 | |
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| 1.0349 | 12.9955 | 718 | 0.3209 | 0.4346 | 0.0825 | |
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| 0.8498 | 13.9910 | 773 | 0.3147 | 0.4300 | 0.0818 | |
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| 0.7259 | 14.9864 | 828 | 0.3151 | 0.4054 | 0.0742 | |
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| 0.6193 | 16.0 | 884 | 0.3132 | 0.4200 | 0.0748 | |
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| 0.5381 | 16.9955 | 939 | 0.3256 | 0.3895 | 0.0711 | |
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| 0.4792 | 17.9910 | 994 | 0.3441 | 0.3863 | 0.0699 | |
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| 0.4266 | 18.9864 | 1049 | 0.3323 | 0.3855 | 0.0692 | |
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| 0.3717 | 20.0 | 1105 | 0.3396 | 0.3871 | 0.0671 | |
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| 0.3503 | 20.9955 | 1160 | 0.3394 | 0.3772 | 0.0679 | |
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| 0.3254 | 21.9910 | 1215 | 0.3383 | 0.3868 | 0.0682 | |
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| 0.2808 | 22.9864 | 1270 | 0.3784 | 0.3808 | 0.0684 | |
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| 0.2534 | 24.0 | 1326 | 0.3449 | 0.3629 | 0.0652 | |
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| 0.2467 | 24.9955 | 1381 | 0.3540 | 0.3725 | 0.0664 | |
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| 0.2271 | 25.9910 | 1436 | 0.3677 | 0.3512 | 0.0630 | |
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| 0.2197 | 26.9864 | 1491 | 0.3623 | 0.3664 | 0.0645 | |
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| 0.2041 | 28.0 | 1547 | 0.3791 | 0.3950 | 0.0653 | |
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| 0.2013 | 28.9955 | 1602 | 0.3656 | 0.3515 | 0.0619 | |
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| 0.1877 | 29.9910 | 1657 | 0.3700 | 0.3533 | 0.0632 | |
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| 0.1763 | 30.9864 | 1712 | 0.3907 | 0.3594 | 0.0638 | |
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| 0.1651 | 32.0 | 1768 | 0.3825 | 0.3713 | 0.0652 | |
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| 0.1697 | 32.9955 | 1823 | 0.3777 | 0.3546 | 0.0624 | |
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| 0.1699 | 33.9910 | 1878 | 0.4016 | 0.3536 | 0.0631 | |
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| 0.1553 | 34.9864 | 1933 | 0.4027 | 0.3547 | 0.0620 | |
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| 0.1438 | 36.0 | 1989 | 0.4027 | 0.3444 | 0.0612 | |
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| 0.1526 | 36.9955 | 2044 | 0.4131 | 0.3510 | 0.0613 | |
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| 0.1388 | 37.9910 | 2099 | 0.3921 | 0.3594 | 0.0617 | |
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| 0.1334 | 38.9864 | 2154 | 0.3944 | 0.3519 | 0.0614 | |
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| 0.1269 | 40.0 | 2210 | 0.4067 | 0.3486 | 0.0611 | |
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| 0.1332 | 40.9955 | 2265 | 0.3779 | 0.3416 | 0.0594 | |
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| 0.1239 | 41.9910 | 2320 | 0.4081 | 0.3432 | 0.0603 | |
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| 0.1172 | 42.9864 | 2375 | 0.3946 | 0.3356 | 0.0587 | |
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| 0.1174 | 44.0 | 2431 | 0.4208 | 0.3333 | 0.0582 | |
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| 0.1168 | 44.9955 | 2486 | 0.3811 | 0.3297 | 0.0585 | |
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| 0.1118 | 45.9910 | 2541 | 0.4092 | 0.3406 | 0.0596 | |
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| 0.1061 | 46.9864 | 2596 | 0.4050 | 0.3248 | 0.0573 | |
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| 0.1019 | 48.0 | 2652 | 0.4025 | 0.3250 | 0.0572 | |
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| 0.0959 | 48.9955 | 2707 | 0.4168 | 0.3306 | 0.0579 | |
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| 0.102 | 49.9910 | 2762 | 0.4353 | 0.3300 | 0.0571 | |
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| 0.0967 | 50.9864 | 2817 | 0.4308 | 0.3307 | 0.0587 | |
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| 0.0953 | 52.0 | 2873 | 0.4258 | 0.3227 | 0.0567 | |
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| 0.0936 | 52.9955 | 2928 | 0.4012 | 0.3262 | 0.0555 | |
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| 0.0917 | 53.9910 | 2983 | 0.4252 | 0.3219 | 0.0549 | |
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| 0.0851 | 54.9864 | 3038 | 0.4243 | 0.3331 | 0.0570 | |
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| 0.0829 | 56.0 | 3094 | 0.4353 | 0.3224 | 0.0558 | |
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| 0.0761 | 56.9955 | 3149 | 0.4437 | 0.3299 | 0.0569 | |
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| 0.074 | 57.9910 | 3204 | 0.4178 | 0.3231 | 0.0551 | |
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| 0.0731 | 58.9864 | 3259 | 0.4297 | 0.3249 | 0.0560 | |
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| 0.0683 | 60.0 | 3315 | 0.4271 | 0.3215 | 0.0549 | |
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| 0.0698 | 60.9955 | 3370 | 0.4462 | 0.3197 | 0.0539 | |
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| 0.0722 | 61.9910 | 3425 | 0.4369 | 0.3157 | 0.0535 | |
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| 0.0654 | 62.9864 | 3480 | 0.4259 | 0.3208 | 0.0545 | |
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| 0.0653 | 64.0 | 3536 | 0.4431 | 0.3169 | 0.0544 | |
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| 0.0636 | 64.9955 | 3591 | 0.4397 | 0.3149 | 0.0535 | |
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| 0.0619 | 65.9910 | 3646 | 0.4410 | 0.3195 | 0.0549 | |
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| 0.0622 | 66.9864 | 3701 | 0.4306 | 0.3199 | 0.0545 | |
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| 0.0558 | 68.0 | 3757 | 0.4444 | 0.3099 | 0.0534 | |
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| 0.0595 | 68.9955 | 3812 | 0.4487 | 0.3123 | 0.0530 | |
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| 0.0558 | 69.9910 | 3867 | 0.4535 | 0.3110 | 0.0534 | |
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| 0.0487 | 70.9864 | 3922 | 0.4498 | 0.3105 | 0.0530 | |
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| 0.0512 | 72.0 | 3978 | 0.4411 | 0.3073 | 0.0524 | |
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| 0.0496 | 72.9955 | 4033 | 0.4345 | 0.3135 | 0.0533 | |
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| 0.0505 | 73.9910 | 4088 | 0.4520 | 0.3080 | 0.0521 | |
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| 0.0431 | 74.9864 | 4143 | 0.4432 | 0.3044 | 0.0518 | |
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| 0.0456 | 76.0 | 4199 | 0.4548 | 0.2995 | 0.0514 | |
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| 0.045 | 76.9955 | 4254 | 0.4503 | 0.2997 | 0.0505 | |
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| 0.0443 | 77.9910 | 4309 | 0.4552 | 0.3042 | 0.0517 | |
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| 0.0435 | 78.9864 | 4364 | 0.4646 | 0.2986 | 0.0505 | |
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| 0.0407 | 80.0 | 4420 | 0.4461 | 0.3075 | 0.0509 | |
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| 0.0396 | 80.9955 | 4475 | 0.4507 | 0.3031 | 0.0510 | |
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| 0.0401 | 81.9910 | 4530 | 0.4454 | 0.3023 | 0.0508 | |
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| 0.0352 | 82.9864 | 4585 | 0.4473 | 0.2991 | 0.0503 | |
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| 0.0328 | 84.0 | 4641 | 0.4550 | 0.3067 | 0.0515 | |
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| 0.037 | 84.9955 | 4696 | 0.4513 | 0.2971 | 0.0502 | |
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| 0.0358 | 85.9910 | 4751 | 0.4447 | 0.2955 | 0.0497 | |
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| 0.034 | 86.9864 | 4806 | 0.4504 | 0.2952 | 0.0496 | |
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| 0.0313 | 88.0 | 4862 | 0.4674 | 0.2965 | 0.0500 | |
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| 0.0269 | 88.9955 | 4917 | 0.4620 | 0.2967 | 0.0496 | |
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| 0.0304 | 89.9910 | 4972 | 0.4541 | 0.2927 | 0.0490 | |
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| 0.029 | 90.9864 | 5027 | 0.4503 | 0.2958 | 0.0492 | |
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| 0.0293 | 92.0 | 5083 | 0.4555 | 0.2935 | 0.0492 | |
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| 0.027 | 92.9955 | 5138 | 0.4598 | 0.2955 | 0.0491 | |
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| 0.0285 | 93.9910 | 5193 | 0.4629 | 0.2946 | 0.0492 | |
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| 0.0279 | 94.9864 | 5248 | 0.4582 | 0.2933 | 0.0490 | |
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| 0.0264 | 96.0 | 5304 | 0.4576 | 0.2916 | 0.0490 | |
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| 0.0258 | 96.9955 | 5359 | 0.4605 | 0.2933 | 0.0491 | |
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| 0.0247 | 97.9910 | 5414 | 0.4591 | 0.2948 | 0.0491 | |
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| 0.0226 | 98.9864 | 5469 | 0.4610 | 0.2952 | 0.0492 | |
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| 0.0226 | 99.5475 | 5500 | 0.4610 | 0.2945 | 0.0491 | |
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### Framework versions |
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- Transformers 4.47.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.0.2 |
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- Tokenizers 0.20.1 |
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