End of training

README.md

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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