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DelaliScratchwerk
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time-period-classifier-bert

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
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End of training

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  1. README.md +13 -13
  2. model.safetensors +1 -1
  3. 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 [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1557
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- - Accuracy: 0.5
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- - F1 Macro: 0.4947
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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- | No log | 1.0 | 12 | 1.7889 | 0.1667 | 0.0476 |
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- | No log | 2.0 | 24 | 1.6388 | 0.25 | 0.1816 |
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- | No log | 3.0 | 36 | 1.3442 | 0.3667 | 0.3330 |
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- | No log | 4.0 | 48 | 1.3157 | 0.4167 | 0.4037 |
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- | 1.4557 | 5.0 | 60 | 1.0837 | 0.5167 | 0.5161 |
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- | 1.4557 | 6.0 | 72 | 1.1564 | 0.4833 | 0.4770 |
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- | 1.4557 | 7.0 | 84 | 1.0700 | 0.5 | 0.4987 |
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- | 1.4557 | 8.0 | 96 | 1.1798 | 0.4833 | 0.4701 |
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- | 0.4397 | 9.0 | 108 | 1.1566 | 0.5 | 0.4785 |
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- | 0.4397 | 10.0 | 120 | 1.1557 | 0.5 | 0.4947 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1907
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+ - Accuracy: 0.9674
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+ - F1 Macro: 0.9683
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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+ | 1.1962 | 1.0 | 120 | 0.8911 | 0.6576 | 0.6000 |
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+ | 0.8928 | 2.0 | 240 | 0.5397 | 0.7935 | 0.7938 |
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+ | 0.565 | 3.0 | 360 | 0.4020 | 0.8605 | 0.8618 |
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+ | 0.3721 | 4.0 | 480 | 0.2893 | 0.9094 | 0.9092 |
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+ | 0.2123 | 5.0 | 600 | 0.2099 | 0.9438 | 0.9428 |
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+ | 0.1374 | 6.0 | 720 | 0.1425 | 0.9692 | 0.9698 |
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+ | 0.0682 | 7.0 | 840 | 0.1796 | 0.9656 | 0.9663 |
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+ | 0.0451 | 8.0 | 960 | 0.1928 | 0.9674 | 0.9683 |
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+ | 0.0275 | 9.0 | 1080 | 0.1870 | 0.9656 | 0.9666 |
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+ | 0.0224 | 10.0 | 1200 | 0.1907 | 0.9674 | 0.9683 |
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  ### Framework versions
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