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---
license: cc-by-4.0
base_model: allegro/herbert-large-cased
tags:
- generated_from_trainer
datasets:
- universal_dependencies
model-index:
- name: herbert-large-cased_deprel
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# herbert-large-cased_deprel
This model is a fine-tuned version of [allegro/herbert-large-cased](https://huggingface.co./allegro/herbert-large-cased) on the universal_dependencies dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4494
- : {'precision': 0.9848484848484849, 'recall': 0.9154929577464789, 'f1': 0.948905109489051, 'number': 71}
- Arataxis:insert: {'precision': 0.6216216216216216, 'recall': 0.34328358208955223, 'f1': 0.4423076923076923, 'number': 67}
- Arataxis:obj: {'precision': 0.6428571428571429, 'recall': 0.46551724137931033, 'f1': 0.5399999999999999, 'number': 58}
- Ark: {'precision': 0.8614457831325302, 'recall': 0.7944444444444444, 'f1': 0.8265895953757226, 'number': 180}
- Ase: {'precision': 0.9363103953147877, 'recall': 0.900070372976777, 'f1': 0.9178327951202009, 'number': 1421}
- Bj: {'precision': 0.8612244897959184, 'recall': 0.8115384615384615, 'f1': 0.8356435643564357, 'number': 520}
- Bl: {'precision': 0.8, 'recall': 0.8054054054054054, 'f1': 0.8026936026936028, 'number': 740}
- Bl:agent: {'precision': 0.6875, 'recall': 0.6875, 'f1': 0.6875, 'number': 16}
- Bl:arg: {'precision': 0.7847222222222222, 'recall': 0.710691823899371, 'f1': 0.7458745874587458, 'number': 318}
- Bl:cmpr: {'precision': 0.8461538461538461, 'recall': 0.6470588235294118, 'f1': 0.7333333333333334, 'number': 17}
- C: {'precision': 0.8974358974358975, 'recall': 0.8115942028985508, 'f1': 0.8523592085235921, 'number': 345}
- C:preconj: {'precision': 1.0, 'recall': 0.3333333333333333, 'f1': 0.5, 'number': 6}
- Cl: {'precision': 0.8581081081081081, 'recall': 0.8141025641025641, 'f1': 0.8355263157894737, 'number': 156}
- Cl:relcl: {'precision': 0.7368421052631579, 'recall': 0.5526315789473685, 'f1': 0.631578947368421, 'number': 76}
- Comp: {'precision': 0.7606382978723404, 'recall': 0.7079207920792079, 'f1': 0.7333333333333332, 'number': 202}
- Comp:cleft: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 4}
- Comp:obj: {'precision': 0.5, 'recall': 0.2916666666666667, 'f1': 0.3684210526315789, 'number': 24}
- Comp:pred: {'precision': 0.4375, 'recall': 0.7, 'f1': 0.5384615384615384, 'number': 10}
- Comp:subj: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Dvcl: {'precision': 0.7983193277310925, 'recall': 0.7480314960629921, 'f1': 0.7723577235772359, 'number': 127}
- Dvcl:cmpr: {'precision': 0.3333333333333333, 'recall': 0.25, 'f1': 0.28571428571428575, 'number': 4}
- Dvmod: {'precision': 0.8131868131868132, 'recall': 0.7789473684210526, 'f1': 0.7956989247311829, 'number': 380}
- Dvmod:arg: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 4}
- Dvmod:emph: {'precision': 0.7755102040816326, 'recall': 0.7354838709677419, 'f1': 0.7549668874172186, 'number': 155}
- Dvmod:neg: {'precision': 0.9067796610169492, 'recall': 0.8492063492063492, 'f1': 0.8770491803278689, 'number': 126}
- Et: {'precision': 0.9072164948453608, 'recall': 0.7927927927927928, 'f1': 0.8461538461538461, 'number': 111}
- Et:numgov: {'precision': 0.8421052631578947, 'recall': 0.8, 'f1': 0.8205128205128205, 'number': 20}
- Et:nummod: {'precision': 0.5, 'recall': 1.0, 'f1': 0.6666666666666666, 'number': 1}
- Et:poss: {'precision': 0.8928571428571429, 'recall': 0.8620689655172413, 'f1': 0.8771929824561403, 'number': 58}
- Iscourse:intj: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}
- Ist: {'precision': 1.0, 'recall': 0.6666666666666666, 'f1': 0.8, 'number': 9}
- Ixed: {'precision': 0.6833333333333333, 'recall': 0.47674418604651164, 'f1': 0.5616438356164384, 'number': 86}
- Lat: {'precision': 0.6724137931034483, 'recall': 0.5416666666666666, 'f1': 0.6, 'number': 72}
- Mod: {'precision': 0.7808471454880295, 'recall': 0.7138047138047138, 'f1': 0.7458223394898855, 'number': 1188}
- Mod:arg: {'precision': 0.5681818181818182, 'recall': 0.4878048780487805, 'f1': 0.5249343832020996, 'number': 205}
- Mod:flat: {'precision': 0.5609756097560976, 'recall': 0.3898305084745763, 'f1': 0.46, 'number': 59}
- Mod:poss: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 4}
- Mod:pred: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Obj: {'precision': 0.7905759162303665, 'recall': 0.6832579185520362, 'f1': 0.733009708737864, 'number': 221}
- Ocative: {'precision': 0.75, 'recall': 0.9, 'f1': 0.8181818181818182, 'number': 10}
- Onj: {'precision': 0.7920792079207921, 'recall': 0.6517311608961304, 'f1': 0.7150837988826816, 'number': 491}
- Oot: {'precision': 0.955, 'recall': 0.955, 'f1': 0.955, 'number': 1000}
- Op: {'precision': 0.7974683544303798, 'recall': 0.7682926829268293, 'f1': 0.782608695652174, 'number': 82}
- Ppos: {'precision': 0.7272727272727273, 'recall': 0.5423728813559322, 'f1': 0.6213592233009708, 'number': 59}
- Rphan: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
- Subj: {'precision': 0.9121287128712872, 'recall': 0.8826347305389222, 'f1': 0.8971393791844188, 'number': 835}
- Subj:pass: {'precision': 0.7727272727272727, 'recall': 0.5862068965517241, 'f1': 0.6666666666666667, 'number': 29}
- Ummod: {'precision': 0.8769230769230769, 'recall': 0.890625, 'f1': 0.883720930232558, 'number': 64}
- Ummod:gov: {'precision': 0.7346938775510204, 'recall': 0.72, 'f1': 0.7272727272727272, 'number': 50}
- Unct: {'precision': 0.9216317767042405, 'recall': 0.8516865079365079, 'f1': 0.8852797112657901, 'number': 2016}
- Ux: {'precision': 0.9166666666666666, 'recall': 0.6111111111111112, 'f1': 0.7333333333333334, 'number': 36}
- Ux:clitic: {'precision': 0.9473684210526315, 'recall': 0.9, 'f1': 0.9230769230769231, 'number': 60}
- Ux:cnd: {'precision': 0.8, 'recall': 0.7272727272727273, 'f1': 0.761904761904762, 'number': 22}
- Ux:imp: {'precision': 1.0, 'recall': 0.75, 'f1': 0.8571428571428571, 'number': 4}
- Ux:pass: {'precision': 0.7297297297297297, 'recall': 0.6923076923076923, 'f1': 0.7105263157894737, 'number': 39}
- Xpl:pv: {'precision': 0.8973214285714286, 'recall': 0.8410041841004184, 'f1': 0.8682505399568035, 'number': 239}
- Overall Precision: 0.8599
- Overall Recall: 0.7975
- Overall F1: 0.8275
- Overall Accuracy: 0.8468
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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