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roberta-best-finetuned-hopes-fears

Text Classification
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roberta
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jamiehudson/roberta-best-finetuned-hopes-fears

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  1. README.md +20 -20
  2. model.safetensors +1 -1
  3. runs/May31_19-51-17_68d233ee17d4/events.out.tfevents.1717185090.68d233ee17d4.2835.3 +3 -0
  4. tokenizer.json +2 -14
  5. training_args.bin +1 -1
README.md CHANGED
@@ -17,18 +17,18 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5676
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- - Accuracy: 0.9534
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- - F1 Weighted: 0.9543
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- - Precision Hopes: 0.7022
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  - Recall Hopes: 0.7622
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- - F1 Hopes: 0.7310
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- - Precision Fears: 0.8740
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  - Recall Fears: 0.9328
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- - F1 Fears: 0.9024
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- - Precision Neither: 0.9804
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- - Recall Neither: 0.9699
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- - F1 Neither: 0.9751
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  ## Model description
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@@ -61,16 +61,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Weighted | Precision Hopes | Recall Hopes | F1 Hopes | Precision Fears | Recall Fears | F1 Fears | Precision Neither | Recall Neither | F1 Neither |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:-----------------:|:--------------:|:----------:|
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- | No log | 1.0 | 171 | 1.0349 | 0.8791 | 0.8226 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8791 | 1.0 | 0.9357 |
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- | 0.9414 | 2.0 | 342 | 0.3255 | 0.9218 | 0.9264 | 0.5810 | 0.7439 | 0.6524 | 0.6792 | 0.9076 | 0.7770 | 0.9777 | 0.9368 | 0.9568 |
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- | 0.9414 | 3.0 | 513 | 0.2678 | 0.8697 | 0.8897 | 0.3817 | 0.9146 | 0.5386 | 0.6886 | 0.9664 | 0.8042 | 0.9944 | 0.8605 | 0.9226 |
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- | 0.2918 | 4.0 | 684 | 0.2523 | 0.9124 | 0.9238 | 0.4608 | 0.8963 | 0.6087 | 0.8740 | 0.9328 | 0.9024 | 0.9910 | 0.9125 | 0.9502 |
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- | 0.2918 | 5.0 | 855 | 0.2868 | 0.9368 | 0.9413 | 0.5787 | 0.8293 | 0.6817 | 0.8485 | 0.9412 | 0.8924 | 0.9853 | 0.9451 | 0.9648 |
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- | 0.1436 | 6.0 | 1026 | 0.3765 | 0.9475 | 0.9501 | 0.6415 | 0.8293 | 0.7234 | 0.8672 | 0.9328 | 0.8988 | 0.9850 | 0.9577 | 0.9712 |
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- | 0.1436 | 7.0 | 1197 | 0.3750 | 0.9308 | 0.9372 | 0.5492 | 0.8841 | 0.6776 | 0.8129 | 0.9496 | 0.8760 | 0.9912 | 0.9334 | 0.9615 |
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- | 0.0673 | 8.0 | 1368 | 0.5053 | 0.9517 | 0.9532 | 0.6825 | 0.7866 | 0.7309 | 0.8626 | 0.9496 | 0.904 | 0.9827 | 0.9650 | 0.9738 |
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- | 0.0345 | 9.0 | 1539 | 0.5717 | 0.9539 | 0.9546 | 0.7168 | 0.7561 | 0.7359 | 0.8496 | 0.9496 | 0.8968 | 0.9808 | 0.9699 | 0.9753 |
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- | 0.0345 | 10.0 | 1710 | 0.5676 | 0.9534 | 0.9543 | 0.7022 | 0.7622 | 0.7310 | 0.8740 | 0.9328 | 0.9024 | 0.9804 | 0.9699 | 0.9751 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6120
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+ - Accuracy: 0.9496
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+ - F1 Weighted: 0.9509
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+ - Precision Hopes: 0.6757
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  - Recall Hopes: 0.7622
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+ - F1 Hopes: 0.7163
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+ - Precision Fears: 0.8672
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  - Recall Fears: 0.9328
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+ - F1 Fears: 0.8988
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+ - Precision Neither: 0.9798
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+ - Recall Neither: 0.9655
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+ - F1 Neither: 0.9726
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Weighted | Precision Hopes | Recall Hopes | F1 Hopes | Precision Fears | Recall Fears | F1 Fears | Precision Neither | Recall Neither | F1 Neither |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:-----------------:|:--------------:|:----------:|
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+ | No log | 1.0 | 171 | 1.0201 | 0.8791 | 0.8226 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8791 | 1.0 | 0.9357 |
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+ | 0.9075 | 2.0 | 342 | 0.3018 | 0.9146 | 0.9220 | 0.5251 | 0.8293 | 0.6430 | 0.7020 | 0.8908 | 0.7852 | 0.9834 | 0.9227 | 0.9521 |
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+ | 0.9075 | 3.0 | 513 | 0.2450 | 0.9141 | 0.9229 | 0.4947 | 0.8476 | 0.6247 | 0.7724 | 0.9412 | 0.8485 | 0.9864 | 0.9179 | 0.9509 |
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+ | 0.2782 | 4.0 | 684 | 0.3093 | 0.9402 | 0.9436 | 0.6 | 0.8232 | 0.6941 | 0.9182 | 0.8487 | 0.8821 | 0.9796 | 0.9548 | 0.9670 |
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+ | 0.2782 | 5.0 | 855 | 0.2838 | 0.9030 | 0.9145 | 0.4744 | 0.9024 | 0.6218 | 0.6970 | 0.9664 | 0.8099 | 0.9930 | 0.8994 | 0.9439 |
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+ | 0.1561 | 6.0 | 1026 | 0.4644 | 0.9479 | 0.9495 | 0.6548 | 0.7866 | 0.7147 | 0.9273 | 0.8571 | 0.8908 | 0.9774 | 0.9660 | 0.9717 |
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+ | 0.1561 | 7.0 | 1197 | 0.4976 | 0.9496 | 0.9512 | 0.6788 | 0.7988 | 0.7339 | 0.8516 | 0.9160 | 0.8826 | 0.9817 | 0.9636 | 0.9725 |
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+ | 0.0743 | 8.0 | 1368 | 0.5949 | 0.9517 | 0.9528 | 0.6978 | 0.7744 | 0.7341 | 0.8651 | 0.9160 | 0.8898 | 0.9798 | 0.9679 | 0.9738 |
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+ | 0.0297 | 9.0 | 1539 | 0.5912 | 0.9483 | 0.9498 | 0.6649 | 0.7622 | 0.7102 | 0.8615 | 0.9412 | 0.8996 | 0.9802 | 0.9636 | 0.9718 |
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+ | 0.0297 | 10.0 | 1710 | 0.6120 | 0.9496 | 0.9509 | 0.6757 | 0.7622 | 0.7163 | 0.8672 | 0.9328 | 0.8988 | 0.9798 | 0.9655 | 0.9726 |
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  ### Framework versions
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