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req_mod_ner_modelv2

Token Classification
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PyTorch
Dutch
roberta
Generated from Trainer
Inference Endpoints
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@@ -10,6 +10,12 @@ metrics:
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  model-index:
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  - name: req_mod_ner_modelv2
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  results: []
 
 
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -19,10 +25,10 @@ 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-ner](https://huggingface.co/pdelobelle/robbert-v2-dutch-ner) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6759
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- - Precision: 0.7112
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- - Recall: 0.7644
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- - F1: 0.7368
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  - Accuracy: 0.9261
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  ## Model description
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  - lr_scheduler_type: linear
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  - num_epochs: 16
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 270 | 0.4543 | 0.6111 | 0.6322 | 0.6215 | 0.8989 |
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- | 0.4703 | 2.0 | 540 | 0.4260 | 0.5129 | 0.6839 | 0.5862 | 0.8740 |
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- | 0.4703 | 3.0 | 810 | 0.3841 | 0.6034 | 0.6207 | 0.6119 | 0.9020 |
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- | 0.1808 | 4.0 | 1080 | 0.5177 | 0.6124 | 0.6264 | 0.6193 | 0.8974 |
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- | 0.1808 | 5.0 | 1350 | 0.4433 | 0.6911 | 0.7586 | 0.7233 | 0.9168 |
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- | 0.0933 | 6.0 | 1620 | 0.4377 | 0.7207 | 0.7414 | 0.7309 | 0.9253 |
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- | 0.0933 | 7.0 | 1890 | 0.5752 | 0.6333 | 0.6552 | 0.6441 | 0.9114 |
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- | 0.0551 | 8.0 | 2160 | 0.5671 | 0.6684 | 0.7529 | 0.7081 | 0.9191 |
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- | 0.0551 | 9.0 | 2430 | 0.5356 | 0.6862 | 0.7414 | 0.7127 | 0.9253 |
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- | 0.0394 | 10.0 | 2700 | 0.6103 | 0.6736 | 0.7471 | 0.7084 | 0.9152 |
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- | 0.0394 | 11.0 | 2970 | 0.6029 | 0.6885 | 0.7241 | 0.7059 | 0.9246 |
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- | 0.0286 | 12.0 | 3240 | 0.5353 | 0.6995 | 0.7356 | 0.7171 | 0.9277 |
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- | 0.0219 | 13.0 | 3510 | 0.6057 | 0.7120 | 0.7529 | 0.7318 | 0.9261 |
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- | 0.0219 | 14.0 | 3780 | 0.6601 | 0.7167 | 0.7414 | 0.7288 | 0.9261 |
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- | 0.0144 | 15.0 | 4050 | 0.6678 | 0.7090 | 0.7701 | 0.7383 | 0.9261 |
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- | 0.0144 | 16.0 | 4320 | 0.6759 | 0.7112 | 0.7644 | 0.7368 | 0.9261 |
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-
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  ### Framework versions
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  model-index:
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  - name: req_mod_ner_modelv2
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  results: []
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+ widget:
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+ - text: "De Oplossing ondersteunt het zoeken op de metadata van zaken, documenten en objecten en op gegevens uit de basisregistraties die gekoppeld zijn aan een zaak."
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+ - text: "De Oplossing ondersteunt parafering en het plaatsen van een gecertificeerde elektronische handtekening."
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+ - text: "De Aangeboden oplossing stelt de medewerker in staat een zaak te registreren."
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+ - text: "Het Financieel systeem heeft functionaliteit om een debiteurenadministratie te voeren."
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+ - text: "Als gebruiker wil ik dat de oplossing mij naar zaken laat zoeken op basis van zaaknummer, zaaktitel, omschrijving en datum."
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-ner](https://huggingface.co/pdelobelle/robbert-v2-dutch-ner) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6678
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+ - Precision: 0.7090
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+ - Recall: 0.7701
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+ - F1: 0.7383
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  - Accuracy: 0.9261
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  ## Model description
 
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  - lr_scheduler_type: linear
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  - num_epochs: 16
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+ ### Evaluation results
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+
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+ | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.6678 | 0.7090 | 0.7701 | 0.7383 | 0.9261 |
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 240 | 0.4780 | 0.3456 | 0.4052 | 0.3730 | 0.8789 |
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+ | No log | 2.0 | 480 | 0.3903 | 0.5934 | 0.4655 | 0.5217 | 0.9080 |
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+ | 0.4168 | 3.0 | 720 | 0.5082 | 0.6782 | 0.5086 | 0.5813 | 0.9169 |
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+ | 0.4168 | 4.0 | 960 | 0.4307 | 0.5846 | 0.6552 | 0.6179 | 0.9201 |
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+ | 0.1633 | 5.0 | 1200 | 0.5179 | 0.6 | 0.5948 | 0.5974 | 0.9233 |
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+ | 0.1633 | 6.0 | 1440 | 0.6073 | 0.5752 | 0.5603 | 0.5677 | 0.9185 |
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+ | 0.0676 | 7.0 | 1680 | 0.6198 | 0.6638 | 0.6638 | 0.6638 | 0.9233 |
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+ | 0.0676 | 8.0 | 1920 | 0.6876 | 0.6311 | 0.6638 | 0.6471 | 0.9185 |
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+ | 0.0445 | 9.0 | 2160 | 0.7112 | 0.6522 | 0.6466 | 0.6494 | 0.9201 |
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+ | 0.0445 | 10.0 | 2400 | 0.7232 | 0.6522 | 0.6466 | 0.6494 | 0.9193 |
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+ | 0.0259 | 11.0 | 2640 | 0.6511 | 0.6371 | 0.6810 | 0.6583 | 0.9233 |
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+ | 0.0259 | 12.0 | 2880 | 0.6733 | 0.6783 | 0.6724 | 0.6753 | 0.9257 |
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+ | 0.0146 | 13.0 | 3120 | 0.6636 | 0.6695 | 0.6810 | 0.6752 | 0.9282 |
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+ | 0.0146 | 14.0 | 3360 | 0.6943 | 0.6496 | 0.6552 | 0.6524 | 0.9257 |
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+ | 0.0134 | 15.0 | 3600 | 0.7055 | 0.6552 | 0.6552 | 0.6552 | 0.9257 |
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+ | 0.0134 | 16.0 | 3840 | 0.7115 | 0.6522 | 0.6466 | 0.6494 | 0.9249 |
 
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  ### Framework versions
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