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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- xtreme_s |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod10 |
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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: xtreme_s |
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type: xtreme_s |
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config: fleurs.id_id |
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split: test |
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args: fleurs.id_id |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.9609339919173776 |
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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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# wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod10 |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the xtreme_s dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.5424 |
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- Wer: 0.9609 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 9.2693 | 1.0 | 39 | 3.1721 | 1.0 | |
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| 2.9485 | 2.0 | 78 | 2.8726 | 1.0 | |
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| 2.8943 | 3.0 | 117 | 2.8655 | 1.0 | |
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| 2.9036 | 4.0 | 156 | 2.8631 | 1.0 | |
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| 2.8869 | 5.0 | 195 | 2.8614 | 1.0 | |
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| 2.8802 | 6.0 | 234 | 2.8854 | 1.0 | |
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| 2.8802 | 7.0 | 273 | 2.8515 | 1.0 | |
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| 2.8706 | 8.0 | 312 | 2.8609 | 1.0 | |
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| 2.8712 | 9.0 | 351 | 2.8458 | 1.0 | |
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| 2.8583 | 10.0 | 390 | 2.8361 | 1.0 | |
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| 2.857 | 11.0 | 429 | 2.8355 | 1.0 | |
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| 2.8546 | 12.0 | 468 | 2.8439 | 1.0 | |
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| 2.8463 | 13.0 | 507 | 2.8348 | 1.0 | |
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| 2.8307 | 14.0 | 546 | 2.7596 | 1.0 | |
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| 2.7673 | 15.0 | 585 | 2.6289 | 1.0 | |
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| 2.5597 | 16.0 | 624 | 2.3411 | 1.0 | |
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| 2.224 | 17.0 | 663 | 2.0992 | 1.0 | |
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| 2.0145 | 18.0 | 702 | 1.7290 | 1.0 | |
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| 1.7274 | 19.0 | 741 | 1.5571 | 0.9954 | |
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| 1.6774 | 20.0 | 780 | 1.4439 | 0.9906 | |
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| 1.4585 | 21.0 | 819 | 1.3841 | 1.1238 | |
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| 1.342 | 22.0 | 858 | 1.2805 | 0.9662 | |
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| 1.215 | 23.0 | 897 | 1.2965 | 0.9628 | |
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| 1.188 | 24.0 | 936 | 1.2713 | 0.9659 | |
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| 1.1147 | 25.0 | 975 | 1.2936 | 1.0251 | |
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| 1.0374 | 26.0 | 1014 | 1.2900 | 0.9483 | |
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| 0.9352 | 27.0 | 1053 | 1.3671 | 0.9908 | |
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| 0.9249 | 28.0 | 1092 | 1.3018 | 0.9404 | |
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| 0.7973 | 29.0 | 1131 | 1.3253 | 0.9631 | |
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| 0.7451 | 30.0 | 1170 | 1.4314 | 1.0451 | |
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| 0.7391 | 31.0 | 1209 | 1.4553 | 0.9909 | |
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| 0.699 | 32.0 | 1248 | 1.5116 | 0.9487 | |
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| 0.5484 | 33.0 | 1287 | 1.5492 | 0.9829 | |
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| 0.5106 | 34.0 | 1326 | 1.6631 | 1.0674 | |
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| 0.5989 | 35.0 | 1365 | 1.6305 | 1.0150 | |
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| 0.464 | 36.0 | 1404 | 1.6285 | 0.9430 | |
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| 0.4925 | 37.0 | 1443 | 1.7208 | 1.0183 | |
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| 0.4206 | 38.0 | 1482 | 1.7476 | 1.0040 | |
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| 0.3848 | 39.0 | 1521 | 1.8125 | 1.0341 | |
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| 0.4057 | 40.0 | 1560 | 1.8245 | 0.9750 | |
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| 0.3978 | 41.0 | 1599 | 1.7153 | 0.9326 | |
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| 0.3806 | 42.0 | 1638 | 1.8650 | 1.0025 | |
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| 0.3376 | 43.0 | 1677 | 1.9067 | 0.9653 | |
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| 0.3798 | 44.0 | 1716 | 2.0028 | 0.9396 | |
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| 0.2902 | 45.0 | 1755 | 2.0901 | 0.9920 | |
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| 0.3324 | 46.0 | 1794 | 1.8935 | 0.9729 | |
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| 0.3241 | 47.0 | 1833 | 2.0133 | 1.0074 | |
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| 0.3055 | 48.0 | 1872 | 2.0352 | 0.9943 | |
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| 0.2927 | 49.0 | 1911 | 1.9539 | 1.0022 | |
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| 0.2729 | 50.0 | 1950 | 2.0982 | 0.9910 | |
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| 0.2569 | 51.0 | 1989 | 2.1607 | 0.9832 | |
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| 0.2683 | 52.0 | 2028 | 2.2544 | 0.9705 | |
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| 0.2685 | 53.0 | 2067 | 2.1528 | 0.9857 | |
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| 0.2757 | 54.0 | 2106 | 2.1648 | 0.9490 | |
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| 0.2379 | 55.0 | 2145 | 2.2498 | 0.9693 | |
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| 0.2501 | 56.0 | 2184 | 2.2509 | 1.0282 | |
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| 0.2347 | 57.0 | 2223 | 2.2095 | 0.9897 | |
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| 0.2697 | 58.0 | 2262 | 2.1933 | 0.9695 | |
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| 0.2255 | 59.0 | 2301 | 2.2140 | 0.9756 | |
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| 0.2071 | 60.0 | 2340 | 2.2364 | 0.9787 | |
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| 0.228 | 61.0 | 2379 | 2.3069 | 0.9551 | |
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| 0.2112 | 62.0 | 2418 | 2.3191 | 0.9769 | |
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| 0.2224 | 63.0 | 2457 | 2.2679 | 1.0025 | |
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| 0.2081 | 64.0 | 2496 | 2.2548 | 0.9660 | |
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| 0.2149 | 65.0 | 2535 | 2.1813 | 0.9720 | |
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| 0.2156 | 66.0 | 2574 | 2.0609 | 0.9633 | |
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| 0.1916 | 67.0 | 2613 | 2.4192 | 0.9594 | |
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| 0.2221 | 68.0 | 2652 | 2.3571 | 1.0186 | |
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| 0.1849 | 69.0 | 2691 | 2.3650 | 0.9705 | |
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| 0.1999 | 70.0 | 2730 | 2.3588 | 0.9700 | |
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| 0.2314 | 71.0 | 2769 | 2.5680 | 1.0693 | |
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| 0.1995 | 72.0 | 2808 | 2.3918 | 1.0490 | |
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| 0.1842 | 73.0 | 2847 | 2.3448 | 0.9706 | |
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| 0.1841 | 74.0 | 2886 | 2.3811 | 0.9945 | |
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| 0.1836 | 75.0 | 2925 | 2.4134 | 0.9659 | |
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| 0.1844 | 76.0 | 2964 | 2.3892 | 0.9657 | |
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| 0.1933 | 77.0 | 3003 | 2.3327 | 0.9606 | |
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| 0.1757 | 78.0 | 3042 | 2.4641 | 0.9702 | |
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| 0.1794 | 79.0 | 3081 | 2.4175 | 0.9535 | |
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| 0.1795 | 80.0 | 3120 | 2.3742 | 0.9503 | |
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| 0.1859 | 81.0 | 3159 | 2.5093 | 0.9508 | |
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| 0.1641 | 82.0 | 3198 | 2.4232 | 0.9647 | |
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| 0.195 | 83.0 | 3237 | 2.4070 | 0.9474 | |
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| 0.1712 | 84.0 | 3276 | 2.4726 | 0.9674 | |
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| 0.1882 | 85.0 | 3315 | 2.4682 | 0.9643 | |
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| 0.1746 | 86.0 | 3354 | 2.4826 | 0.9523 | |
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| 0.1655 | 87.0 | 3393 | 2.5652 | 0.9495 | |
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| 0.1895 | 88.0 | 3432 | 2.4967 | 0.9489 | |
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| 0.1659 | 89.0 | 3471 | 2.4620 | 0.9695 | |
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| 0.1618 | 90.0 | 3510 | 2.4974 | 0.9433 | |
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| 0.1559 | 91.0 | 3549 | 2.5137 | 0.9599 | |
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| 0.1646 | 92.0 | 3588 | 2.4645 | 0.9579 | |
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| 0.1599 | 93.0 | 3627 | 2.4751 | 0.9612 | |
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| 0.1735 | 94.0 | 3666 | 2.5473 | 0.9597 | |
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| 0.1571 | 95.0 | 3705 | 2.5158 | 0.9675 | |
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| 0.1606 | 96.0 | 3744 | 2.5234 | 0.9645 | |
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| 0.1499 | 97.0 | 3783 | 2.5328 | 0.9612 | |
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| 0.1571 | 98.0 | 3822 | 2.5535 | 0.9594 | |
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| 0.166 | 99.0 | 3861 | 2.5450 | 0.9592 | |
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| 0.1651 | 100.0 | 3900 | 2.5424 | 0.9609 | |
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### Framework versions |
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- Transformers 4.39.2 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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