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andreaceto
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schedulebot-nlu-engine

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distilbert
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End of training

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  1. README.md +54 -54
  2. model.safetensors +1 -1
  3. runs/Jul18_13-22-10_ffb539b2fe97/events.out.tfevents.1752844931.ffb539b2fe97.389.1 +0 -0
  4. training_args.bin +0 -0
README.md CHANGED
@@ -16,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3449
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- - Intent Accuracy: 0.9041
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- - Intent F1: 0.9042
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- - Ner F1: 0.9290
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  ## Model description
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@@ -50,56 +50,56 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Intent Accuracy | Intent F1 | Ner F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:---------------:|:---------:|:------:|
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- | 1.0412 | 1.0 | 64 | 0.7080 | 0.8082 | 0.8089 | 0.9251 |
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- | 1.0113 | 2.0 | 128 | 0.6668 | 0.8219 | 0.8216 | 0.9239 |
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- | 0.9423 | 3.0 | 192 | 0.6392 | 0.8219 | 0.8204 | 0.9274 |
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- | 0.8935 | 4.0 | 256 | 0.6043 | 0.8425 | 0.8420 | 0.9264 |
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- | 0.854 | 5.0 | 320 | 0.5867 | 0.8470 | 0.8469 | 0.9252 |
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- | 0.8108 | 6.0 | 384 | 0.5579 | 0.8470 | 0.8457 | 0.9264 |
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- | 0.7891 | 7.0 | 448 | 0.5471 | 0.8470 | 0.8470 | 0.9269 |
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- | 0.7521 | 8.0 | 512 | 0.5301 | 0.8402 | 0.8391 | 0.9270 |
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- | 0.7534 | 9.0 | 576 | 0.5154 | 0.8584 | 0.8583 | 0.9269 |
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- | 0.6927 | 10.0 | 640 | 0.4991 | 0.8516 | 0.8505 | 0.9279 |
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- | 0.6914 | 11.0 | 704 | 0.4868 | 0.8767 | 0.8779 | 0.9274 |
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- | 0.6727 | 12.0 | 768 | 0.4754 | 0.8767 | 0.8775 | 0.9281 |
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- | 0.6331 | 13.0 | 832 | 0.4680 | 0.8584 | 0.8577 | 0.9280 |
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- | 0.6251 | 14.0 | 896 | 0.4588 | 0.8836 | 0.8845 | 0.9280 |
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- | 0.6348 | 15.0 | 960 | 0.4464 | 0.8790 | 0.8798 | 0.9264 |
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- | 0.5997 | 16.0 | 1024 | 0.4476 | 0.8744 | 0.8744 | 0.9274 |
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- | 0.598 | 17.0 | 1088 | 0.4345 | 0.8790 | 0.8771 | 0.9286 |
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- | 0.5725 | 18.0 | 1152 | 0.4292 | 0.8813 | 0.8812 | 0.9281 |
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- | 0.5627 | 19.0 | 1216 | 0.4189 | 0.8790 | 0.8781 | 0.9292 |
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- | 0.5315 | 20.0 | 1280 | 0.4146 | 0.8858 | 0.8857 | 0.9291 |
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- | 0.5451 | 21.0 | 1344 | 0.4041 | 0.8881 | 0.8869 | 0.9291 |
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- | 0.5242 | 22.0 | 1408 | 0.3963 | 0.8904 | 0.8890 | 0.9286 |
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- | 0.5348 | 23.0 | 1472 | 0.3918 | 0.8950 | 0.8929 | 0.9292 |
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- | 0.5132 | 24.0 | 1536 | 0.3954 | 0.8973 | 0.8974 | 0.9291 |
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- | 0.5011 | 25.0 | 1600 | 0.3875 | 0.8995 | 0.8991 | 0.9286 |
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- | 0.4971 | 26.0 | 1664 | 0.3799 | 0.8950 | 0.8936 | 0.9291 |
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- | 0.4837 | 27.0 | 1728 | 0.3786 | 0.8950 | 0.8951 | 0.9285 |
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- | 0.472 | 28.0 | 1792 | 0.3740 | 0.9064 | 0.9061 | 0.9291 |
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- | 0.4696 | 29.0 | 1856 | 0.3733 | 0.8973 | 0.8963 | 0.9291 |
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- | 0.4598 | 30.0 | 1920 | 0.3711 | 0.9018 | 0.9018 | 0.9285 |
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- | 0.4562 | 31.0 | 1984 | 0.3702 | 0.8995 | 0.8986 | 0.9296 |
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- | 0.4687 | 32.0 | 2048 | 0.3674 | 0.9064 | 0.9059 | 0.9291 |
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- | 0.4473 | 33.0 | 2112 | 0.3621 | 0.9110 | 0.9103 | 0.9285 |
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- | 0.4583 | 34.0 | 2176 | 0.3584 | 0.9087 | 0.9078 | 0.9285 |
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- | 0.4512 | 35.0 | 2240 | 0.3563 | 0.9041 | 0.9036 | 0.9285 |
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- | 0.4504 | 36.0 | 2304 | 0.3570 | 0.9041 | 0.9032 | 0.9285 |
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- | 0.4398 | 37.0 | 2368 | 0.3550 | 0.9041 | 0.9042 | 0.9290 |
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- | 0.4352 | 38.0 | 2432 | 0.3535 | 0.9064 | 0.9067 | 0.9285 |
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- | 0.4227 | 39.0 | 2496 | 0.3506 | 0.9087 | 0.9090 | 0.9295 |
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- | 0.4256 | 40.0 | 2560 | 0.3499 | 0.9087 | 0.9088 | 0.9290 |
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- | 0.4207 | 41.0 | 2624 | 0.3489 | 0.9064 | 0.9062 | 0.9290 |
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- | 0.4266 | 42.0 | 2688 | 0.3463 | 0.9110 | 0.9105 | 0.9290 |
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- | 0.426 | 43.0 | 2752 | 0.3472 | 0.9110 | 0.9108 | 0.9290 |
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- | 0.4193 | 44.0 | 2816 | 0.3462 | 0.9110 | 0.9108 | 0.9290 |
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- | 0.4112 | 45.0 | 2880 | 0.3464 | 0.9087 | 0.9085 | 0.9295 |
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- | 0.4206 | 46.0 | 2944 | 0.3460 | 0.9087 | 0.9084 | 0.9290 |
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- | 0.4206 | 47.0 | 3008 | 0.3454 | 0.9064 | 0.9062 | 0.9290 |
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- | 0.406 | 48.0 | 3072 | 0.3447 | 0.9041 | 0.9042 | 0.9290 |
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- | 0.4048 | 49.0 | 3136 | 0.3449 | 0.9041 | 0.9042 | 0.9290 |
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- | 0.3956 | 50.0 | 3200 | 0.3449 | 0.9041 | 0.9042 | 0.9290 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3576
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+ - Intent Accuracy: 0.9110
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+ - Intent F1: 0.9109
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+ - Ner F1: 0.6897
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Intent Accuracy | Intent F1 | Ner F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:---------------:|:---------:|:------:|
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+ | 1.115 | 1.0 | 64 | 0.7159 | 0.8059 | 0.8059 | 0.6490 |
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+ | 1.0456 | 2.0 | 128 | 0.6909 | 0.8105 | 0.8104 | 0.6545 |
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+ | 0.966 | 3.0 | 192 | 0.6603 | 0.8151 | 0.8141 | 0.6656 |
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+ | 0.924 | 4.0 | 256 | 0.6358 | 0.8265 | 0.8260 | 0.6711 |
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+ | 0.9042 | 5.0 | 320 | 0.6084 | 0.8242 | 0.8249 | 0.6765 |
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+ | 0.8602 | 6.0 | 384 | 0.5821 | 0.8379 | 0.8383 | 0.6743 |
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+ | 0.811 | 7.0 | 448 | 0.5633 | 0.8516 | 0.8508 | 0.6765 |
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+ | 0.8068 | 8.0 | 512 | 0.5532 | 0.8447 | 0.8457 | 0.6711 |
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+ | 0.772 | 9.0 | 576 | 0.5326 | 0.8516 | 0.8523 | 0.6765 |
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+ | 0.7349 | 10.0 | 640 | 0.5132 | 0.8676 | 0.8671 | 0.6765 |
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+ | 0.7047 | 11.0 | 704 | 0.5053 | 0.8630 | 0.8622 | 0.6798 |
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+ | 0.6994 | 12.0 | 768 | 0.4976 | 0.8630 | 0.8625 | 0.6809 |
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+ | 0.6831 | 13.0 | 832 | 0.4860 | 0.8630 | 0.8635 | 0.6820 |
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+ | 0.6509 | 14.0 | 896 | 0.4741 | 0.8858 | 0.8858 | 0.6809 |
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+ | 0.643 | 15.0 | 960 | 0.4616 | 0.8836 | 0.8833 | 0.6820 |
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+ | 0.6392 | 16.0 | 1024 | 0.4562 | 0.8858 | 0.8860 | 0.6832 |
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+ | 0.5852 | 17.0 | 1088 | 0.4452 | 0.8836 | 0.8833 | 0.6874 |
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+ | 0.5854 | 18.0 | 1152 | 0.4374 | 0.8813 | 0.8812 | 0.6885 |
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+ | 0.5917 | 19.0 | 1216 | 0.4358 | 0.8858 | 0.8851 | 0.6897 |
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+ | 0.5678 | 20.0 | 1280 | 0.4298 | 0.8927 | 0.8922 | 0.6875 |
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+ | 0.5684 | 21.0 | 1344 | 0.4229 | 0.9064 | 0.9061 | 0.6865 |
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+ | 0.5594 | 22.0 | 1408 | 0.4111 | 0.9041 | 0.9042 | 0.6853 |
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+ | 0.5556 | 23.0 | 1472 | 0.4058 | 0.8995 | 0.8995 | 0.6853 |
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+ | 0.521 | 24.0 | 1536 | 0.4058 | 0.8904 | 0.8902 | 0.6853 |
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+ | 0.5224 | 25.0 | 1600 | 0.3999 | 0.9041 | 0.9041 | 0.6853 |
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+ | 0.5269 | 26.0 | 1664 | 0.3923 | 0.9110 | 0.9109 | 0.6875 |
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+ | 0.4832 | 27.0 | 1728 | 0.3916 | 0.9064 | 0.9066 | 0.6853 |
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+ | 0.4938 | 28.0 | 1792 | 0.3908 | 0.9041 | 0.9041 | 0.6853 |
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+ | 0.4819 | 29.0 | 1856 | 0.3851 | 0.9064 | 0.9061 | 0.6853 |
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+ | 0.4781 | 30.0 | 1920 | 0.3916 | 0.9041 | 0.9041 | 0.6853 |
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+ | 0.4671 | 31.0 | 1984 | 0.3799 | 0.9041 | 0.9042 | 0.6875 |
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+ | 0.4689 | 32.0 | 2048 | 0.3810 | 0.9041 | 0.9042 | 0.6875 |
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+ | 0.4799 | 33.0 | 2112 | 0.3759 | 0.9064 | 0.9066 | 0.6897 |
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+ | 0.4691 | 34.0 | 2176 | 0.3699 | 0.9110 | 0.9107 | 0.6897 |
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+ | 0.4752 | 35.0 | 2240 | 0.3699 | 0.9087 | 0.9082 | 0.6918 |
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+ | 0.4574 | 36.0 | 2304 | 0.3676 | 0.9132 | 0.9132 | 0.6897 |
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+ | 0.4654 | 37.0 | 2368 | 0.3668 | 0.9132 | 0.9134 | 0.6918 |
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+ | 0.4416 | 38.0 | 2432 | 0.3663 | 0.9110 | 0.9112 | 0.6918 |
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+ | 0.4433 | 39.0 | 2496 | 0.3685 | 0.9110 | 0.9111 | 0.6897 |
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+ | 0.4202 | 40.0 | 2560 | 0.3625 | 0.9155 | 0.9156 | 0.6897 |
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+ | 0.4523 | 41.0 | 2624 | 0.3595 | 0.9178 | 0.9176 | 0.6897 |
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+ | 0.4325 | 42.0 | 2688 | 0.3589 | 0.9178 | 0.9176 | 0.6897 |
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+ | 0.4406 | 43.0 | 2752 | 0.3600 | 0.9087 | 0.9085 | 0.6897 |
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+ | 0.4348 | 44.0 | 2816 | 0.3594 | 0.9132 | 0.9130 | 0.6875 |
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+ | 0.4339 | 45.0 | 2880 | 0.3573 | 0.9178 | 0.9176 | 0.6897 |
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+ | 0.4259 | 46.0 | 2944 | 0.3576 | 0.9132 | 0.9131 | 0.6897 |
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+ | 0.4272 | 47.0 | 3008 | 0.3568 | 0.9155 | 0.9153 | 0.6897 |
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+ | 0.4276 | 48.0 | 3072 | 0.3568 | 0.9155 | 0.9153 | 0.6897 |
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+ | 0.4297 | 49.0 | 3136 | 0.3575 | 0.9132 | 0.9131 | 0.6897 |
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+ | 0.4223 | 50.0 | 3200 | 0.3576 | 0.9110 | 0.9109 | 0.6897 |
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  ### Framework versions
model.safetensors CHANGED
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training_args.bin CHANGED
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