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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_12-35-02_d35699767f5b/events.out.tfevents.1752842103.d35699767f5b.539.1 +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: 0.3685
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- - Intent Accuracy: 0.9132
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- - Intent F1: 0.9128
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- - Ner F1: 0.9255
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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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- | 1.0518 | 1.0 | 64 | 0.6730 | 0.8151 | 0.8147 | 0.9153 |
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- | 0.9965 | 2.0 | 128 | 0.6458 | 0.8219 | 0.8217 | 0.9176 |
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- | 0.9344 | 3.0 | 192 | 0.6251 | 0.8265 | 0.8259 | 0.9181 |
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- | 0.8837 | 4.0 | 256 | 0.5905 | 0.8288 | 0.8283 | 0.9192 |
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- | 0.8614 | 5.0 | 320 | 0.5697 | 0.8470 | 0.8464 | 0.9184 |
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- | 0.7958 | 6.0 | 384 | 0.5637 | 0.8333 | 0.8335 | 0.9178 |
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- | 0.7729 | 7.0 | 448 | 0.5383 | 0.8379 | 0.8363 | 0.9190 |
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- | 0.7564 | 8.0 | 512 | 0.5250 | 0.8607 | 0.8606 | 0.9195 |
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- | 0.7342 | 9.0 | 576 | 0.5082 | 0.8493 | 0.8488 | 0.9201 |
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- | 0.7095 | 10.0 | 640 | 0.5058 | 0.8562 | 0.8553 | 0.9181 |
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- | 0.69 | 11.0 | 704 | 0.4996 | 0.8653 | 0.8646 | 0.9181 |
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- | 0.6732 | 12.0 | 768 | 0.4954 | 0.8516 | 0.8501 | 0.9195 |
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- | 0.6615 | 13.0 | 832 | 0.4703 | 0.8562 | 0.8558 | 0.9182 |
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- | 0.6669 | 14.0 | 896 | 0.4638 | 0.8721 | 0.8724 | 0.9192 |
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- | 0.6227 | 15.0 | 960 | 0.4543 | 0.8790 | 0.8783 | 0.9204 |
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- | 0.6185 | 16.0 | 1024 | 0.4453 | 0.8767 | 0.8758 | 0.9217 |
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- | 0.5853 | 17.0 | 1088 | 0.4440 | 0.8676 | 0.8671 | 0.9222 |
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- | 0.5685 | 18.0 | 1152 | 0.4395 | 0.8858 | 0.8851 | 0.9233 |
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- | 0.5691 | 19.0 | 1216 | 0.4351 | 0.8767 | 0.8764 | 0.9217 |
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- | 0.5561 | 20.0 | 1280 | 0.4266 | 0.8813 | 0.8802 | 0.9215 |
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- | 0.5721 | 21.0 | 1344 | 0.4178 | 0.8790 | 0.8788 | 0.9209 |
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- | 0.5091 | 22.0 | 1408 | 0.4136 | 0.8836 | 0.8833 | 0.9209 |
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- | 0.5356 | 23.0 | 1472 | 0.4113 | 0.8858 | 0.8850 | 0.9211 |
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- | 0.526 | 24.0 | 1536 | 0.4083 | 0.8836 | 0.8826 | 0.9206 |
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- | 0.5132 | 25.0 | 1600 | 0.4022 | 0.8995 | 0.8997 | 0.9222 |
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- | 0.5017 | 26.0 | 1664 | 0.3996 | 0.8927 | 0.8925 | 0.9232 |
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- | 0.4926 | 27.0 | 1728 | 0.4006 | 0.8904 | 0.8905 | 0.9220 |
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- | 0.4878 | 28.0 | 1792 | 0.3973 | 0.9018 | 0.9018 | 0.9237 |
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- | 0.5028 | 29.0 | 1856 | 0.3968 | 0.8950 | 0.8944 | 0.9243 |
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- | 0.4519 | 30.0 | 1920 | 0.3921 | 0.8950 | 0.8946 | 0.9232 |
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- | 0.4718 | 31.0 | 1984 | 0.3879 | 0.9041 | 0.9039 | 0.9232 |
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- | 0.4551 | 32.0 | 2048 | 0.3873 | 0.8995 | 0.8991 | 0.9238 |
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- | 0.4696 | 33.0 | 2112 | 0.3819 | 0.9064 | 0.9064 | 0.9244 |
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- | 0.4655 | 34.0 | 2176 | 0.3830 | 0.9018 | 0.9011 | 0.925 |
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- | 0.4421 | 35.0 | 2240 | 0.3814 | 0.9018 | 0.9013 | 0.9249 |
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- | 0.4455 | 36.0 | 2304 | 0.3790 | 0.9041 | 0.9034 | 0.9256 |
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- | 0.4521 | 37.0 | 2368 | 0.3795 | 0.9064 | 0.9058 | 0.9245 |
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- | 0.451 | 38.0 | 2432 | 0.3772 | 0.9132 | 0.9129 | 0.9245 |
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- | 0.4581 | 39.0 | 2496 | 0.3781 | 0.9064 | 0.9060 | 0.9245 |
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- | 0.44 | 40.0 | 2560 | 0.3735 | 0.9132 | 0.9129 | 0.9245 |
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- | 0.4259 | 41.0 | 2624 | 0.3729 | 0.9110 | 0.9105 | 0.9251 |
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- | 0.4273 | 42.0 | 2688 | 0.3724 | 0.9132 | 0.9129 | 0.9255 |
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- | 0.4484 | 43.0 | 2752 | 0.3730 | 0.9110 | 0.9104 | 0.925 |
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- | 0.418 | 44.0 | 2816 | 0.3705 | 0.9132 | 0.9128 | 0.925 |
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- | 0.4197 | 45.0 | 2880 | 0.3688 | 0.9132 | 0.9131 | 0.925 |
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- | 0.4411 | 46.0 | 2944 | 0.3696 | 0.9132 | 0.9129 | 0.9245 |
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- | 0.4251 | 47.0 | 3008 | 0.3695 | 0.9132 | 0.9128 | 0.9245 |
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- | 0.4313 | 48.0 | 3072 | 0.3685 | 0.9110 | 0.9106 | 0.9245 |
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- | 0.4305 | 49.0 | 3136 | 0.3685 | 0.9132 | 0.9128 | 0.9255 |
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- | 0.4158 | 50.0 | 3200 | 0.3685 | 0.9132 | 0.9128 | 0.9255 |
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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: 0.3449
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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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  | 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
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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Binary file (38.4 kB). View file
 
training_args.bin CHANGED
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