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Token Classification
Transformers
Safetensors
modernbert
Generated from Trainer
Model card Files
xet
 Community
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End of training

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  1. README.md +10 -10
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [jhu-clsp/mmBERT-base](https://huggingface.co/jhu-clsp/mmBERT-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5605
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- - Precision: 0.6597
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- - Recall: 0.7133
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- - F1: 0.6854
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- - Accuracy: 0.8019
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.5891 | 1.0 | 438 | 0.5828 | 0.6346 | 0.7095 | 0.6699 | 0.7956 |
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- | 0.5574 | 2.0 | 876 | 0.5660 | 0.6413 | 0.7165 | 0.6768 | 0.7999 |
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- | 0.5403 | 3.0 | 1314 | 0.5605 | 0.6597 | 0.7133 | 0.6854 | 0.8019 |
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- | 0.4933 | 4.0 | 1752 | 0.5716 | 0.6611 | 0.7005 | 0.6802 | 0.7957 |
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- | 0.435 | 5.0 | 2190 | 0.6148 | 0.6517 | 0.7002 | 0.6751 | 0.7878 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [jhu-clsp/mmBERT-base](https://huggingface.co/jhu-clsp/mmBERT-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5621
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+ - Precision: 0.6665
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+ - Recall: 0.7278
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+ - F1: 0.6958
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+ - Accuracy: 0.8007
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.5954 | 1.0 | 438 | 0.5941 | 0.6576 | 0.7258 | 0.6900 | 0.7933 |
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+ | 0.5723 | 2.0 | 876 | 0.5671 | 0.6890 | 0.6954 | 0.6922 | 0.7971 |
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+ | 0.5241 | 3.0 | 1314 | 0.5621 | 0.6665 | 0.7278 | 0.6958 | 0.8007 |
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+ | 0.4738 | 4.0 | 1752 | 0.5869 | 0.6598 | 0.7013 | 0.6799 | 0.7853 |
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+ | 0.4159 | 5.0 | 2190 | 0.6157 | 0.6581 | 0.7088 | 0.6825 | 0.7910 |
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  ### Framework versions
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