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sianbrumm
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Ner_Productname

Token Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
Inference Endpoints
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sianbrumm/productname_ner_model

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Files changed (7) hide show
  1. README.md +61 -1
  2. config.json +59 -63
  3. model.safetensors +3 -0
  4. special_tokens_map.json +7 -1
  5. tokenizer.json +0 -0
  6. tokenizer_config.json +58 -1
  7. training_args.bin +2 -2
README.md CHANGED
@@ -1,3 +1,63 @@
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  ---
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- license: unknown
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ license: mit
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+ base_model: dbmdz/bert-base-german-uncased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: first_ner_model
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+ results: []
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  ---
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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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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # first_ner_model
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+
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+ This model is a fine-tuned version of [dbmdz/bert-base-german-uncased](https://huggingface.co/dbmdz/bert-base-german-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6659
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+ - Label Metrics: {'Alcohol_content': {'precision': 0.5172413793103449, 'recall': 0.7894736842105263, 'f1': 0.625, 'number': 19}, 'Brand': {'precision': 0.8753623188405797, 'recall': 0.9082706766917293, 'f1': 0.8915129151291513, 'number': 665}, 'Packaging.Quantity': {'precision': 0.6891891891891891, 'recall': 0.796875, 'f1': 0.7391304347826088, 'number': 64}, 'Packaging.Type': {'precision': 0.6, 'recall': 0.3, 'f1': 0.4, 'number': 20}, 'Packaging.Volume': {'precision': 0.978494623655914, 'recall': 0.7054263565891473, 'f1': 0.8198198198198199, 'number': 129}, 'Packaging.Weight': {'precision': 0.8891402714932126, 'recall': 0.9974619289340102, 'f1': 0.9401913875598087, 'number': 394}, 'Producttype': {'precision': 0.4715984147952444, 'recall': 0.5344311377245509, 'f1': 0.5010526315789474, 'number': 668}, '_': {'precision': 0.367983367983368, 'recall': 0.42857142857142855, 'f1': 0.3959731543624161, 'number': 413}, 'overall_precision': 0.657608695652174, 'overall_recall': 0.7141652613827993, 'overall_f1': 0.6847210994341149, 'overall_accuracy': 0.7419354838709677}
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+ - Overall Metrics: {'overall_precision': 0.657608695652174, 'overall_recall': 0.7141652613827993, 'overall_f1': 0.6847210994341149, 'overall_accuracy': 0.7419354838709677}
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Label Metrics | Overall Metrics |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------:|
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+ | No log | 1.0 | 175 | 0.6684 | {'Alcohol_content': {'precision': 0.46153846153846156, 'recall': 0.3157894736842105, 'f1': 0.37499999999999994, 'number': 19}, 'Brand': {'precision': 0.8885672937771346, 'recall': 0.9233082706766917, 'f1': 0.9056047197640117, 'number': 665}, 'Packaging.Quantity': {'precision': 0.7272727272727273, 'recall': 0.75, 'f1': 0.7384615384615384, 'number': 64}, 'Packaging.Type': {'precision': 0.6666666666666666, 'recall': 0.1, 'f1': 0.1739130434782609, 'number': 20}, 'Packaging.Volume': {'precision': 0.9782608695652174, 'recall': 0.6976744186046512, 'f1': 0.8144796380090498, 'number': 129}, 'Packaging.Weight': {'precision': 0.8828828828828829, 'recall': 0.9949238578680203, 'f1': 0.9355608591885441, 'number': 394}, 'Producttype': {'precision': 0.43159203980099503, 'recall': 0.5194610778443114, 'f1': 0.4714673913043478, 'number': 668}, '_': {'precision': 0.3300970873786408, 'recall': 0.4116222760290557, 'f1': 0.3663793103448276, 'number': 413}, 'overall_precision': 0.6350837138508372, 'overall_recall': 0.7036256323777403, 'overall_f1': 0.6676, 'overall_accuracy': 0.7299687825182102} | {'overall_precision': 0.6350837138508372, 'overall_recall': 0.7036256323777403, 'overall_f1': 0.6676, 'overall_accuracy': 0.7299687825182102} |
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+ | No log | 2.0 | 350 | 0.6659 | {'Alcohol_content': {'precision': 0.5172413793103449, 'recall': 0.7894736842105263, 'f1': 0.625, 'number': 19}, 'Brand': {'precision': 0.8753623188405797, 'recall': 0.9082706766917293, 'f1': 0.8915129151291513, 'number': 665}, 'Packaging.Quantity': {'precision': 0.6891891891891891, 'recall': 0.796875, 'f1': 0.7391304347826088, 'number': 64}, 'Packaging.Type': {'precision': 0.6, 'recall': 0.3, 'f1': 0.4, 'number': 20}, 'Packaging.Volume': {'precision': 0.978494623655914, 'recall': 0.7054263565891473, 'f1': 0.8198198198198199, 'number': 129}, 'Packaging.Weight': {'precision': 0.8891402714932126, 'recall': 0.9974619289340102, 'f1': 0.9401913875598087, 'number': 394}, 'Producttype': {'precision': 0.4715984147952444, 'recall': 0.5344311377245509, 'f1': 0.5010526315789474, 'number': 668}, '_': {'precision': 0.367983367983368, 'recall': 0.42857142857142855, 'f1': 0.3959731543624161, 'number': 413}, 'overall_precision': 0.657608695652174, 'overall_recall': 0.7141652613827993, 'overall_f1': 0.6847210994341149, 'overall_accuracy': 0.7419354838709677} | {'overall_precision': 0.657608695652174, 'overall_recall': 0.7141652613827993, 'overall_f1': 0.6847210994341149, 'overall_accuracy': 0.7419354838709677} |
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+ | 0.75 | 3.0 | 525 | 0.6749 | {'Alcohol_content': {'precision': 0.6363636363636364, 'recall': 0.7368421052631579, 'f1': 0.6829268292682926, 'number': 19}, 'Brand': {'precision': 0.9033674963396779, 'recall': 0.9278195488721804, 'f1': 0.9154302670623146, 'number': 665}, 'Packaging.Quantity': {'precision': 0.6619718309859155, 'recall': 0.734375, 'f1': 0.6962962962962963, 'number': 64}, 'Packaging.Type': {'precision': 0.5384615384615384, 'recall': 0.35, 'f1': 0.4242424242424242, 'number': 20}, 'Packaging.Volume': {'precision': 0.9787234042553191, 'recall': 0.7131782945736435, 'f1': 0.8251121076233184, 'number': 129}, 'Packaging.Weight': {'precision': 0.8888888888888888, 'recall': 0.9949238578680203, 'f1': 0.9389221556886227, 'number': 394}, 'Producttype': {'precision': 0.5122615803814714, 'recall': 0.562874251497006, 'f1': 0.536376604850214, 'number': 668}, '_': {'precision': 0.4088235294117647, 'recall': 0.3365617433414044, 'f1': 0.36918990703851257, 'number': 413}, 'overall_precision': 0.7022518765638032, 'overall_recall': 0.7099494097807757, 'overall_f1': 0.7060796645702306, 'overall_accuracy': 0.7419354838709677} | {'overall_precision': 0.7022518765638032, 'overall_recall': 0.7099494097807757, 'overall_f1': 0.7060796645702306, 'overall_accuracy': 0.7419354838709677} |
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+ | 0.75 | 4.0 | 700 | 0.6891 | {'Alcohol_content': {'precision': 0.7142857142857143, 'recall': 0.7894736842105263, 'f1': 0.7500000000000001, 'number': 19}, 'Brand': {'precision': 0.9104258443465492, 'recall': 0.9323308270676691, 'f1': 0.9212481426448736, 'number': 665}, 'Packaging.Quantity': {'precision': 0.6712328767123288, 'recall': 0.765625, 'f1': 0.7153284671532847, 'number': 64}, 'Packaging.Type': {'precision': 0.42105263157894735, 'recall': 0.4, 'f1': 0.41025641025641024, 'number': 20}, 'Packaging.Volume': {'precision': 0.9787234042553191, 'recall': 0.7131782945736435, 'f1': 0.8251121076233184, 'number': 129}, 'Packaging.Weight': {'precision': 0.8888888888888888, 'recall': 0.9949238578680203, 'f1': 0.9389221556886227, 'number': 394}, 'Producttype': {'precision': 0.505464480874317, 'recall': 0.5538922155688623, 'f1': 0.5285714285714285, 'number': 668}, '_': {'precision': 0.4217506631299735, 'recall': 0.38498789346246975, 'f1': 0.40253164556962034, 'number': 413}, 'overall_precision': 0.699343724364233, 'overall_recall': 0.7188026981450253, 'overall_f1': 0.7089397089397088, 'overall_accuracy': 0.7447970863683663} | {'overall_precision': 0.699343724364233, 'overall_recall': 0.7188026981450253, 'overall_f1': 0.7089397089397088, 'overall_accuracy': 0.7447970863683663} |
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+ | 0.75 | 5.0 | 875 | 0.7116 | {'Alcohol_content': {'precision': 0.7142857142857143, 'recall': 0.7894736842105263, 'f1': 0.7500000000000001, 'number': 19}, 'Brand': {'precision': 0.9092240117130308, 'recall': 0.9338345864661655, 'f1': 0.9213649851632048, 'number': 665}, 'Packaging.Quantity': {'precision': 0.7, 'recall': 0.765625, 'f1': 0.7313432835820896, 'number': 64}, 'Packaging.Type': {'precision': 0.5, 'recall': 0.55, 'f1': 0.5238095238095238, 'number': 20}, 'Packaging.Volume': {'precision': 0.968421052631579, 'recall': 0.7131782945736435, 'f1': 0.8214285714285715, 'number': 129}, 'Packaging.Weight': {'precision': 0.8886363636363637, 'recall': 0.9923857868020305, 'f1': 0.9376498800959233, 'number': 394}, 'Producttype': {'precision': 0.5089655172413793, 'recall': 0.5523952095808383, 'f1': 0.529791816223977, 'number': 668}, '_': {'precision': 0.4172661870503597, 'recall': 0.4213075060532688, 'f1': 0.419277108433735, 'number': 413}, 'overall_precision': 0.6963202587949858, 'overall_recall': 0.7259696458684655, 'overall_f1': 0.7108359133126935, 'overall_accuracy': 0.7484391259105099} | {'overall_precision': 0.6963202587949858, 'overall_recall': 0.7259696458684655, 'overall_f1': 0.7108359133126935, 'overall_accuracy': 0.7484391259105099} |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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