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--- |
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base_model: ai-forever/ruBert-large |
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tags: |
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- generated_from_trainer |
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datasets: |
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- universal_dependencies |
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model-index: |
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- name: ruBert-large_deprel |
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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 |
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should probably proofread and complete it, then remove this comment. --> |
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# ruBert-large_deprel |
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This model is a fine-tuned version of [ai-forever/ruBert-large](https://huggingface.co/ai-forever/ruBert-large) on the universal_dependencies dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7246 |
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- : {'precision': 0.6857142857142857, 'recall': 0.6486486486486487, 'f1': 0.6666666666666667, 'number': 37} |
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- Arataxis: {'precision': 0.7638190954773869, 'recall': 0.6816143497757847, 'f1': 0.7203791469194313, 'number': 446} |
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- Ark: {'precision': 0.916923076923077, 'recall': 0.884272997032641, 'f1': 0.9003021148036254, 'number': 337} |
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- Ase: {'precision': 0.9278455284552846, 'recall': 0.9330608073582013, 'f1': 0.9304458598726114, 'number': 1957} |
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- Bj: {'precision': 0.9047619047619048, 'recall': 0.9114391143911439, 'f1': 0.9080882352941176, 'number': 542} |
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- Bl: {'precision': 0.8643478260869565, 'recall': 0.8603577611079054, 'f1': 0.8623481781376519, 'number': 1733} |
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- C: {'precision': 0.9087248322147651, 'recall': 0.8978779840848806, 'f1': 0.9032688458972647, 'number': 754} |
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- Cl: {'precision': 0.8141263940520446, 'recall': 0.8171641791044776, 'f1': 0.8156424581005587, 'number': 268} |
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- Cl:relcl: {'precision': 0.8129496402877698, 'recall': 0.889763779527559, 'f1': 0.849624060150376, 'number': 127} |
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- Comp: {'precision': 0.9117647058823529, 'recall': 0.9004149377593361, 'f1': 0.906054279749478, 'number': 241} |
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- Dvcl: {'precision': 0.8235294117647058, 'recall': 0.8324324324324325, 'f1': 0.8279569892473118, 'number': 185} |
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- Dvmod: {'precision': 0.8639744952178533, 'recall': 0.8648936170212767, 'f1': 0.864433811802233, 'number': 940} |
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- Et: {'precision': 0.9315673289183223, 'recall': 0.9274725274725275, 'f1': 0.9295154185022025, 'number': 455} |
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- Iscourse: {'precision': 1.0, 'recall': 0.7333333333333333, 'f1': 0.846153846153846, 'number': 15} |
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- Ixed: {'precision': 0.872093023255814, 'recall': 0.8571428571428571, 'f1': 0.8645533141210374, 'number': 175} |
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- Lat: {'precision': 1.0, 'recall': 0.7777777777777778, 'f1': 0.8750000000000001, 'number': 9} |
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- Lat:foreign: {'precision': 0.6363636363636364, 'recall': 0.6422018348623854, 'f1': 0.6392694063926941, 'number': 109} |
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- Lat:name: {'precision': 0.6060606060606061, 'recall': 0.5714285714285714, 'f1': 0.588235294117647, 'number': 140} |
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- Mod: {'precision': 0.8624740843123704, 'recall': 0.8553803975325566, 'f1': 0.8589125946317961, 'number': 2918} |
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- Obj: {'precision': 0.9107142857142857, 'recall': 0.8571428571428571, 'f1': 0.8831168831168831, 'number': 119} |
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- Ompound: {'precision': 0.6666666666666666, 'recall': 0.42105263157894735, 'f1': 0.5161290322580646, 'number': 38} |
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- Onj: {'precision': 0.8317349607672189, 'recall': 0.8361086765994742, 'f1': 0.8339160839160839, 'number': 1141} |
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- Oot: {'precision': 0.8993963782696177, 'recall': 0.8948948948948949, 'f1': 0.8971399899648771, 'number': 999} |
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- Op: {'precision': 0.9117647058823529, 'recall': 0.8303571428571429, 'f1': 0.8691588785046729, 'number': 112} |
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- Ppos: {'precision': 0.5403225806451613, 'recall': 0.6600985221674877, 'f1': 0.5942350332594235, 'number': 203} |
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- Rphan: {'precision': 0.5, 'recall': 0.3103448275862069, 'f1': 0.3829787234042554, 'number': 29} |
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- Subj: {'precision': 0.903305785123967, 'recall': 0.9078073089700996, 'f1': 0.9055509527754764, 'number': 1204} |
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- Subj:pass: {'precision': 0.8978494623655914, 'recall': 0.8391959798994975, 'f1': 0.8675324675324676, 'number': 199} |
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- Ummod: {'precision': 0.7381615598885793, 'recall': 0.8412698412698413, 'f1': 0.7863501483679525, 'number': 315} |
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- Ummod:gov: {'precision': 0.7625, 'recall': 0.8026315789473685, 'f1': 0.7820512820512822, 'number': 76} |
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- Unct: {'precision': 0.9231651376146789, 'recall': 0.911406736484574, 'f1': 0.9172482552342971, 'number': 3533} |
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- Ux: {'precision': 0.9230769230769231, 'recall': 0.6, 'f1': 0.7272727272727274, 'number': 20} |
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- Ux:pass: {'precision': 0.9393939393939394, 'recall': 0.9253731343283582, 'f1': 0.9323308270676692, 'number': 67} |
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- Overall Precision: 0.8762 |
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- Overall Recall: 0.8717 |
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- Overall F1: 0.8739 |
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- Overall Accuracy: 0.8881 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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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: 10 |
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### Training results |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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