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robbert-v2-dutch-base-finetuned-emotion

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  1. README.md +53 -53
  2. config.json +12 -12
  3. model.safetensors +1 -1
  4. runs/Jul29_15-35-20_2e599ec76f1c/events.out.tfevents.1722267328.2e599ec76f1c.2677.0 +3 -0
  5. runs/Jul29_15-36-47_2e599ec76f1c/events.out.tfevents.1722267415.2e599ec76f1c.2677.1 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -18,9 +18,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.3544
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- - Accuracy: 0.5
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- - F1: 0.4979
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  ## Model description
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@@ -51,56 +51,56 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 1.5473 | 1.0 | 25 | 1.4282 | 0.41 | 0.2443 |
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- | 1.4157 | 2.0 | 50 | 1.3685 | 0.51 | 0.4314 |
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- | 1.2735 | 3.0 | 75 | 1.3446 | 0.49 | 0.4334 |
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- | 1.0978 | 4.0 | 100 | 1.3769 | 0.49 | 0.4321 |
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- | 0.9143 | 5.0 | 125 | 1.4552 | 0.5 | 0.4328 |
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- | 0.749 | 6.0 | 150 | 1.5571 | 0.49 | 0.4694 |
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- | 0.5994 | 7.0 | 175 | 1.6080 | 0.51 | 0.4851 |
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- | 0.465 | 8.0 | 200 | 1.7913 | 0.47 | 0.4397 |
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- | 0.3393 | 9.0 | 225 | 1.8298 | 0.48 | 0.4775 |
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- | 0.3029 | 10.0 | 250 | 1.8285 | 0.5 | 0.5009 |
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- | 0.2398 | 11.0 | 275 | 1.9645 | 0.46 | 0.4495 |
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- | 0.1693 | 12.0 | 300 | 2.0640 | 0.5 | 0.5089 |
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- | 0.1263 | 13.0 | 325 | 2.1132 | 0.52 | 0.5076 |
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- | 0.0851 | 14.0 | 350 | 2.2995 | 0.5 | 0.4829 |
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- | 0.0808 | 15.0 | 375 | 2.4314 | 0.44 | 0.4592 |
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- | 0.0443 | 16.0 | 400 | 2.3217 | 0.52 | 0.5175 |
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- | 0.0264 | 17.0 | 425 | 2.5998 | 0.48 | 0.4781 |
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- | 0.0186 | 18.0 | 450 | 2.6112 | 0.5 | 0.4961 |
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- | 0.0149 | 19.0 | 475 | 2.6620 | 0.48 | 0.4752 |
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- | 0.0116 | 20.0 | 500 | 2.7490 | 0.48 | 0.4748 |
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- | 0.0114 | 21.0 | 525 | 2.8106 | 0.5 | 0.4907 |
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- | 0.0066 | 22.0 | 550 | 2.9086 | 0.49 | 0.4921 |
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- | 0.0059 | 23.0 | 575 | 2.8579 | 0.5 | 0.4903 |
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- | 0.0101 | 24.0 | 600 | 2.9214 | 0.48 | 0.4717 |
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- | 0.0045 | 25.0 | 625 | 2.9654 | 0.51 | 0.5052 |
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- | 0.0036 | 26.0 | 650 | 2.9763 | 0.52 | 0.5168 |
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- | 0.0072 | 27.0 | 675 | 3.0338 | 0.5 | 0.4947 |
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- | 0.0031 | 28.0 | 700 | 3.0601 | 0.52 | 0.5147 |
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- | 0.0101 | 29.0 | 725 | 3.1009 | 0.49 | 0.4813 |
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- | 0.0027 | 30.0 | 750 | 3.1018 | 0.5 | 0.4921 |
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- | 0.0026 | 31.0 | 775 | 3.1267 | 0.49 | 0.4779 |
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- | 0.0029 | 32.0 | 800 | 3.1425 | 0.51 | 0.5031 |
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- | 0.0023 | 33.0 | 825 | 3.2380 | 0.52 | 0.5186 |
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- | 0.0021 | 34.0 | 850 | 3.2323 | 0.51 | 0.5066 |
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- | 0.0021 | 35.0 | 875 | 3.2950 | 0.51 | 0.5083 |
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- | 0.0022 | 36.0 | 900 | 3.3160 | 0.48 | 0.4768 |
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- | 0.003 | 37.0 | 925 | 3.3565 | 0.49 | 0.4859 |
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- | 0.0018 | 38.0 | 950 | 3.3222 | 0.49 | 0.4846 |
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- | 0.002 | 39.0 | 975 | 3.4573 | 0.5 | 0.5009 |
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- | 0.0019 | 40.0 | 1000 | 3.2969 | 0.49 | 0.4730 |
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- | 0.0017 | 41.0 | 1025 | 3.3766 | 0.49 | 0.4893 |
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- | 0.0017 | 42.0 | 1050 | 3.3572 | 0.49 | 0.4859 |
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- | 0.0016 | 43.0 | 1075 | 3.3027 | 0.49 | 0.4859 |
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- | 0.002 | 44.0 | 1100 | 3.3397 | 0.5 | 0.4965 |
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- | 0.0015 | 45.0 | 1125 | 3.3346 | 0.5 | 0.4965 |
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- | 0.0018 | 46.0 | 1150 | 3.3748 | 0.51 | 0.5085 |
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- | 0.0015 | 47.0 | 1175 | 3.3495 | 0.51 | 0.5073 |
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- | 0.0016 | 48.0 | 1200 | 3.3538 | 0.5 | 0.4979 |
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- | 0.0016 | 49.0 | 1225 | 3.3547 | 0.5 | 0.4979 |
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- | 0.0025 | 50.0 | 1250 | 3.3544 | 0.5 | 0.4979 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on the None dataset.
20
  It achieves the following results on the evaluation set:
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+ - Loss: 3.3545
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+ - Accuracy: 0.52
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+ - F1: 0.5123
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 1.5586 | 1.0 | 25 | 1.4429 | 0.42 | 0.2485 |
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+ | 1.4425 | 2.0 | 50 | 1.3576 | 0.46 | 0.3533 |
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+ | 1.2834 | 3.0 | 75 | 1.3207 | 0.5 | 0.4369 |
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+ | 1.1051 | 4.0 | 100 | 1.3228 | 0.48 | 0.4217 |
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+ | 0.9053 | 5.0 | 125 | 1.3705 | 0.49 | 0.4302 |
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+ | 0.7326 | 6.0 | 150 | 1.4522 | 0.53 | 0.5019 |
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+ | 0.5724 | 7.0 | 175 | 1.5445 | 0.53 | 0.5064 |
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+ | 0.4411 | 8.0 | 200 | 1.6560 | 0.54 | 0.5120 |
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+ | 0.3476 | 9.0 | 225 | 1.7233 | 0.51 | 0.4845 |
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+ | 0.2324 | 10.0 | 250 | 1.9150 | 0.52 | 0.5056 |
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+ | 0.1866 | 11.0 | 275 | 2.0207 | 0.52 | 0.4975 |
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+ | 0.165 | 12.0 | 300 | 2.0863 | 0.52 | 0.5094 |
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+ | 0.1291 | 13.0 | 325 | 2.1584 | 0.5 | 0.4833 |
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+ | 0.0762 | 14.0 | 350 | 2.2296 | 0.55 | 0.5332 |
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+ | 0.0577 | 15.0 | 375 | 2.3171 | 0.5 | 0.4986 |
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+ | 0.0424 | 16.0 | 400 | 2.4509 | 0.5 | 0.4795 |
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+ | 0.0253 | 17.0 | 425 | 2.5444 | 0.49 | 0.4917 |
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+ | 0.0191 | 18.0 | 450 | 2.5894 | 0.51 | 0.5031 |
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+ | 0.0123 | 19.0 | 475 | 2.7144 | 0.5 | 0.4995 |
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+ | 0.01 | 20.0 | 500 | 2.7358 | 0.53 | 0.5231 |
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+ | 0.0086 | 21.0 | 525 | 2.8282 | 0.48 | 0.4825 |
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+ | 0.0064 | 22.0 | 550 | 2.8421 | 0.52 | 0.5244 |
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+ | 0.0059 | 23.0 | 575 | 2.9267 | 0.53 | 0.5200 |
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+ | 0.005 | 24.0 | 600 | 2.9568 | 0.52 | 0.5074 |
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+ | 0.0044 | 25.0 | 625 | 3.0420 | 0.47 | 0.4755 |
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+ | 0.0066 | 26.0 | 650 | 3.0421 | 0.48 | 0.4881 |
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+ | 0.0039 | 27.0 | 675 | 3.1039 | 0.51 | 0.4960 |
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+ | 0.0033 | 28.0 | 700 | 3.1226 | 0.51 | 0.4955 |
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+ | 0.0033 | 29.0 | 725 | 3.1215 | 0.51 | 0.4999 |
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+ | 0.003 | 30.0 | 750 | 3.1649 | 0.51 | 0.4980 |
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+ | 0.0025 | 31.0 | 775 | 3.1716 | 0.5 | 0.4921 |
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+ | 0.0028 | 32.0 | 800 | 3.2371 | 0.5 | 0.4956 |
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+ | 0.0028 | 33.0 | 825 | 3.1730 | 0.52 | 0.5154 |
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+ | 0.0055 | 34.0 | 850 | 3.1842 | 0.49 | 0.4884 |
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+ | 0.0022 | 35.0 | 875 | 3.2324 | 0.51 | 0.4955 |
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+ | 0.0023 | 36.0 | 900 | 3.2221 | 0.52 | 0.5089 |
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+ | 0.002 | 37.0 | 925 | 3.2756 | 0.51 | 0.4981 |
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+ | 0.0021 | 38.0 | 950 | 3.2866 | 0.51 | 0.5010 |
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+ | 0.0019 | 39.0 | 975 | 3.2882 | 0.51 | 0.5010 |
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+ | 0.0018 | 40.0 | 1000 | 3.2864 | 0.51 | 0.4967 |
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+ | 0.0017 | 41.0 | 1025 | 3.3101 | 0.51 | 0.4967 |
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+ | 0.0017 | 42.0 | 1050 | 3.3215 | 0.52 | 0.5089 |
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+ | 0.0016 | 43.0 | 1075 | 3.3253 | 0.51 | 0.5043 |
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+ | 0.0056 | 44.0 | 1100 | 3.3118 | 0.51 | 0.5043 |
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+ | 0.0016 | 45.0 | 1125 | 3.3566 | 0.51 | 0.4981 |
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+ | 0.0016 | 46.0 | 1150 | 3.3593 | 0.51 | 0.4981 |
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+ | 0.0016 | 47.0 | 1175 | 3.3638 | 0.51 | 0.4981 |
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+ | 0.0017 | 48.0 | 1200 | 3.3605 | 0.52 | 0.5089 |
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+ | 0.0017 | 49.0 | 1225 | 3.3526 | 0.52 | 0.5123 |
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+ | 0.0016 | 50.0 | 1250 | 3.3545 | 0.52 | 0.5123 |
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  ### Framework versions
config.json CHANGED
@@ -12,22 +12,22 @@
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  "hidden_dropout_prob": 0.1,
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  "hidden_size": 768,
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  "id2label": {
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- "0": "LABEL_0",
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- "1": "LABEL_1",
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- "2": "LABEL_2",
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- "3": "LABEL_3",
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- "4": "LABEL_4",
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- "5": "LABEL_5"
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  },
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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
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  "label2id": {
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- "LABEL_0": 0,
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- "LABEL_1": 1,
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- "LABEL_2": 2,
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- "LABEL_3": 3,
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- "LABEL_4": 4,
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- "LABEL_5": 5
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  },
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  "layer_norm_eps": 1e-05,
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  "max_position_embeddings": 514,
 
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  "hidden_dropout_prob": 0.1,
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  "hidden_size": 768,
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  "id2label": {
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+ "0": "anger",
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+ "1": "fear",
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+ "2": "joy",
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+ "3": "love",
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+ "4": "neutral",
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+ "5": "sadness"
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  },
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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
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  "label2id": {
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+ "anger": 0,
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+ "fear": 1,
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+ "joy": 2,
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+ "love": 3,
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+ "neutral": 4,
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+ "sadness": 5
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  },
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  "layer_norm_eps": 1e-05,
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  "max_position_embeddings": 514,
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