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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_10-20-53_31557e1a290d/events.out.tfevents.1752834054.31557e1a290d.157.1 +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: 0.3440
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- - Intent Accuracy: 0.9018
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- - Intent F1: 0.9016
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- - Ner F1: 0.9194
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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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- | No log | 1.0 | 64 | 0.6824 | 0.8288 | 0.8286 | 0.9138 |
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- | No log | 2.0 | 128 | 0.6505 | 0.8379 | 0.8375 | 0.9139 |
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- | No log | 3.0 | 192 | 0.6213 | 0.8356 | 0.8349 | 0.9133 |
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- | No log | 4.0 | 256 | 0.6110 | 0.8311 | 0.8320 | 0.9153 |
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- | No log | 5.0 | 320 | 0.5882 | 0.8356 | 0.8374 | 0.9148 |
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- | No log | 6.0 | 384 | 0.5545 | 0.8402 | 0.8399 | 0.9160 |
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- | No log | 7.0 | 448 | 0.5499 | 0.8356 | 0.8360 | 0.9165 |
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- | 0.901 | 8.0 | 512 | 0.5258 | 0.8562 | 0.8556 | 0.9182 |
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- | 0.901 | 9.0 | 576 | 0.5192 | 0.8493 | 0.8500 | 0.9169 |
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- | 0.901 | 10.0 | 640 | 0.4954 | 0.8562 | 0.8559 | 0.9172 |
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- | 0.901 | 11.0 | 704 | 0.4815 | 0.8676 | 0.8671 | 0.9167 |
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- | 0.901 | 12.0 | 768 | 0.4743 | 0.8721 | 0.8723 | 0.9168 |
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- | 0.901 | 13.0 | 832 | 0.4653 | 0.8584 | 0.8589 | 0.9160 |
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- | 0.901 | 14.0 | 896 | 0.4574 | 0.8721 | 0.8723 | 0.9165 |
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- | 0.901 | 15.0 | 960 | 0.4499 | 0.8721 | 0.8714 | 0.9176 |
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- | 0.6846 | 16.0 | 1024 | 0.4343 | 0.8836 | 0.8836 | 0.9167 |
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- | 0.6846 | 17.0 | 1088 | 0.4301 | 0.8813 | 0.8805 | 0.9154 |
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- | 0.6846 | 18.0 | 1152 | 0.4306 | 0.8744 | 0.8748 | 0.9169 |
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- | 0.6846 | 19.0 | 1216 | 0.4218 | 0.8767 | 0.8760 | 0.9176 |
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- | 0.6846 | 20.0 | 1280 | 0.4125 | 0.8881 | 0.8875 | 0.9169 |
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- | 0.6846 | 21.0 | 1344 | 0.4036 | 0.8836 | 0.8829 | 0.9193 |
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- | 0.6846 | 22.0 | 1408 | 0.3975 | 0.8904 | 0.8906 | 0.9187 |
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- | 0.6846 | 23.0 | 1472 | 0.3934 | 0.8927 | 0.8920 | 0.9182 |
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- | 0.5644 | 24.0 | 1536 | 0.3925 | 0.8858 | 0.8853 | 0.9184 |
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- | 0.5644 | 25.0 | 1600 | 0.3863 | 0.8973 | 0.8970 | 0.9159 |
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- | 0.5644 | 26.0 | 1664 | 0.3847 | 0.8927 | 0.8921 | 0.9166 |
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- | 0.5644 | 27.0 | 1728 | 0.3802 | 0.8950 | 0.8945 | 0.9171 |
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- | 0.5644 | 28.0 | 1792 | 0.3755 | 0.8927 | 0.8923 | 0.9176 |
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- | 0.5644 | 29.0 | 1856 | 0.3710 | 0.8950 | 0.8940 | 0.9177 |
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- | 0.5644 | 30.0 | 1920 | 0.3755 | 0.8973 | 0.8969 | 0.9188 |
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- | 0.5644 | 31.0 | 1984 | 0.3641 | 0.8973 | 0.8971 | 0.9194 |
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- | 0.4863 | 32.0 | 2048 | 0.3671 | 0.8973 | 0.8971 | 0.9193 |
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- | 0.4863 | 33.0 | 2112 | 0.3615 | 0.8995 | 0.8992 | 0.9189 |
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- | 0.4863 | 34.0 | 2176 | 0.3591 | 0.8995 | 0.8994 | 0.9199 |
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- | 0.4863 | 35.0 | 2240 | 0.3590 | 0.8881 | 0.8877 | 0.9196 |
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- | 0.4863 | 36.0 | 2304 | 0.3575 | 0.8995 | 0.8992 | 0.9184 |
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- | 0.4863 | 37.0 | 2368 | 0.3569 | 0.9041 | 0.9042 | 0.9204 |
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- | 0.4863 | 38.0 | 2432 | 0.3536 | 0.8995 | 0.8993 | 0.9199 |
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- | 0.4863 | 39.0 | 2496 | 0.3571 | 0.9018 | 0.9018 | 0.9204 |
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- | 0.4571 | 40.0 | 2560 | 0.3479 | 0.9018 | 0.9018 | 0.9195 |
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- | 0.4571 | 41.0 | 2624 | 0.3516 | 0.9018 | 0.9017 | 0.9205 |
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- | 0.4571 | 42.0 | 2688 | 0.3484 | 0.9018 | 0.9016 | 0.9199 |
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- | 0.4571 | 43.0 | 2752 | 0.3490 | 0.9018 | 0.9017 | 0.9194 |
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- | 0.4571 | 44.0 | 2816 | 0.3487 | 0.9018 | 0.9017 | 0.9200 |
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- | 0.4571 | 45.0 | 2880 | 0.3470 | 0.9018 | 0.9016 | 0.9194 |
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- | 0.4571 | 46.0 | 2944 | 0.3454 | 0.8995 | 0.8993 | 0.9194 |
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- | 0.4341 | 47.0 | 3008 | 0.3454 | 0.8973 | 0.8970 | 0.9194 |
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- | 0.4341 | 48.0 | 3072 | 0.3443 | 0.9018 | 0.9016 | 0.9194 |
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- | 0.4341 | 49.0 | 3136 | 0.3444 | 0.9018 | 0.9016 | 0.9194 |
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- | 0.4341 | 50.0 | 3200 | 0.3440 | 0.9018 | 0.9016 | 0.9194 |
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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: 0.3743
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+ - Intent Accuracy: 0.9132
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+ - Intent F1: 0.9132
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+ - Ner F1: 0.9161
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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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+ | 1.0569 | 1.0 | 64 | 0.7285 | 0.8082 | 0.8086 | 0.9076 |
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+ | 1.0159 | 2.0 | 128 | 0.6989 | 0.8128 | 0.8145 | 0.9065 |
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+ | 0.9781 | 3.0 | 192 | 0.6679 | 0.8196 | 0.8185 | 0.9044 |
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+ | 0.9258 | 4.0 | 256 | 0.6406 | 0.8219 | 0.8206 | 0.9054 |
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+ | 0.879 | 5.0 | 320 | 0.6164 | 0.8379 | 0.8390 | 0.9060 |
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+ | 0.8516 | 6.0 | 384 | 0.5951 | 0.8425 | 0.8431 | 0.9066 |
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+ | 0.8276 | 7.0 | 448 | 0.5706 | 0.8470 | 0.8468 | 0.9090 |
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+ | 0.7897 | 8.0 | 512 | 0.5699 | 0.8379 | 0.8390 | 0.9102 |
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+ | 0.7477 | 9.0 | 576 | 0.5442 | 0.8539 | 0.8537 | 0.9099 |
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+ | 0.7443 | 10.0 | 640 | 0.5300 | 0.8562 | 0.8563 | 0.9069 |
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+ | 0.709 | 11.0 | 704 | 0.5254 | 0.8584 | 0.8583 | 0.9099 |
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+ | 0.6971 | 12.0 | 768 | 0.5185 | 0.8607 | 0.8605 | 0.9123 |
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+ | 0.6667 | 13.0 | 832 | 0.4957 | 0.8653 | 0.8650 | 0.9117 |
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+ | 0.6643 | 14.0 | 896 | 0.4860 | 0.8813 | 0.8808 | 0.9083 |
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+ | 0.6274 | 15.0 | 960 | 0.4743 | 0.8813 | 0.8810 | 0.9076 |
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+ | 0.6398 | 16.0 | 1024 | 0.4680 | 0.8790 | 0.8791 | 0.9093 |
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+ | 0.615 | 17.0 | 1088 | 0.4644 | 0.8813 | 0.8810 | 0.9142 |
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+ | 0.6102 | 18.0 | 1152 | 0.4575 | 0.8858 | 0.8859 | 0.9100 |
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+ | 0.5579 | 19.0 | 1216 | 0.4548 | 0.8813 | 0.8813 | 0.9103 |
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+ | 0.5779 | 20.0 | 1280 | 0.4436 | 0.8881 | 0.8881 | 0.9092 |
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+ | 0.5659 | 21.0 | 1344 | 0.4395 | 0.8927 | 0.8925 | 0.9120 |
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+ | 0.5458 | 22.0 | 1408 | 0.4295 | 0.8927 | 0.8930 | 0.9126 |
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+ | 0.5375 | 23.0 | 1472 | 0.4294 | 0.8973 | 0.8974 | 0.9134 |
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+ | 0.5259 | 24.0 | 1536 | 0.4225 | 0.8973 | 0.8972 | 0.9150 |
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+ | 0.5064 | 25.0 | 1600 | 0.4223 | 0.8927 | 0.8930 | 0.9138 |
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+ | 0.5109 | 26.0 | 1664 | 0.4118 | 0.8973 | 0.8971 | 0.9133 |
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+ | 0.5001 | 27.0 | 1728 | 0.4161 | 0.8904 | 0.8902 | 0.9134 |
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+ | 0.5052 | 28.0 | 1792 | 0.4085 | 0.8995 | 0.8994 | 0.9138 |
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+ | 0.4863 | 29.0 | 1856 | 0.4052 | 0.9041 | 0.9041 | 0.9132 |
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+ | 0.4842 | 30.0 | 1920 | 0.4123 | 0.8927 | 0.8927 | 0.9132 |
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+ | 0.474 | 31.0 | 1984 | 0.3944 | 0.9018 | 0.9017 | 0.9138 |
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+ | 0.4638 | 32.0 | 2048 | 0.3946 | 0.9041 | 0.9041 | 0.9148 |
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+ | 0.4678 | 33.0 | 2112 | 0.3989 | 0.8904 | 0.8903 | 0.9133 |
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+ | 0.4641 | 34.0 | 2176 | 0.3920 | 0.9041 | 0.9040 | 0.9150 |
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+ | 0.4632 | 35.0 | 2240 | 0.3884 | 0.9064 | 0.9063 | 0.9145 |
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+ | 0.4825 | 36.0 | 2304 | 0.3882 | 0.9064 | 0.9065 | 0.9138 |
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+ | 0.4403 | 37.0 | 2368 | 0.3854 | 0.8995 | 0.8998 | 0.9134 |
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+ | 0.459 | 38.0 | 2432 | 0.3833 | 0.9041 | 0.9041 | 0.9145 |
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+ | 0.4367 | 39.0 | 2496 | 0.3841 | 0.9064 | 0.9063 | 0.9179 |
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+ | 0.4388 | 40.0 | 2560 | 0.3801 | 0.9041 | 0.9040 | 0.9150 |
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+ | 0.4261 | 41.0 | 2624 | 0.3793 | 0.9087 | 0.9087 | 0.9150 |
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+ | 0.4236 | 42.0 | 2688 | 0.3775 | 0.9064 | 0.9062 | 0.9145 |
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+ | 0.4242 | 43.0 | 2752 | 0.3795 | 0.9064 | 0.9063 | 0.9156 |
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+ | 0.4364 | 44.0 | 2816 | 0.3785 | 0.9041 | 0.9040 | 0.9150 |
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+ | 0.4263 | 45.0 | 2880 | 0.3772 | 0.9041 | 0.9041 | 0.9149 |
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+ | 0.4112 | 46.0 | 2944 | 0.3769 | 0.9041 | 0.9040 | 0.9149 |
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+ | 0.428 | 47.0 | 3008 | 0.3749 | 0.9087 | 0.9085 | 0.9155 |
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+ | 0.4274 | 48.0 | 3072 | 0.3743 | 0.9064 | 0.9062 | 0.9144 |
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+ | 0.4243 | 49.0 | 3136 | 0.3748 | 0.9110 | 0.9109 | 0.9155 |
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+ | 0.4215 | 50.0 | 3200 | 0.3743 | 0.9132 | 0.9132 | 0.9161 |
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  ### Framework versions
model.safetensors CHANGED
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training_args.bin CHANGED
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