---
license: cc-by-4.0
base_model: Goader/liberta-large
tags:
- generated_from_trainer
datasets:
- universal_dependencies
model-index:
- name: Goader_liberta-large-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. -->

# Goader_liberta-large-deprel

This model is a fine-tuned version of [Goader/liberta-large](https://huggingface.co/Goader/liberta-large) on the universal_dependencies dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5901
-  : {'precision': 0.42857142857142855, 'recall': 0.21428571428571427, 'f1': 0.2857142857142857, 'number': 14}
- Arataxis: {'precision': 0.5066666666666667, 'recall': 0.3486238532110092, 'f1': 0.41304347826086957, 'number': 109}
- Arataxis:discourse: {'precision': 0.4117647058823529, 'recall': 0.3684210526315789, 'f1': 0.3888888888888889, 'number': 19}
- Arataxis:rel: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 7}
- Ark: {'precision': 0.8214285714285714, 'recall': 0.7777777777777778, 'f1': 0.7990074441687344, 'number': 207}
- Ase: {'precision': 0.8921023359288098, 'recall': 0.8044132397191575, 'f1': 0.8459915611814346, 'number': 997}
- Bj: {'precision': 0.8446389496717724, 'recall': 0.7524366471734892, 'f1': 0.7958762886597938, 'number': 513}
- Bl: {'precision': 0.8267090620031796, 'recall': 0.7084468664850136, 'f1': 0.7630227439471754, 'number': 734}
- C: {'precision': 0.8328690807799443, 'recall': 0.7310513447432763, 'f1': 0.7786458333333331, 'number': 409}
- Cl: {'precision': 0.7894736842105263, 'recall': 0.3409090909090909, 'f1': 0.4761904761904762, 'number': 44}
- Cl:adv: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 4}
- Cl:relcl: {'precision': 0.7611940298507462, 'recall': 0.7083333333333334, 'f1': 0.7338129496402879, 'number': 144}
- Comp: {'precision': 0.7708333333333334, 'recall': 0.7602739726027398, 'f1': 0.7655172413793104, 'number': 146}
- Comp:sp: {'precision': 0.7931034482758621, 'recall': 0.5897435897435898, 'f1': 0.676470588235294, 'number': 39}
- Dvcl: {'precision': 0.8210526315789474, 'recall': 0.7027027027027027, 'f1': 0.7572815533980582, 'number': 111}
- Dvcl:sp: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
- Dvcl:svc: {'precision': 1.0, 'recall': 0.2, 'f1': 0.33333333333333337, 'number': 5}
- Dvmod: {'precision': 0.8085585585585585, 'recall': 0.7638297872340426, 'f1': 0.7855579868708972, 'number': 470}
- Dvmod:det: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}
- Et: {'precision': 0.8657407407407407, 'recall': 0.7824267782426778, 'f1': 0.8219780219780219, 'number': 239}
- Et:numgov: {'precision': 0.75, 'recall': 0.75, 'f1': 0.75, 'number': 12}
- Et:nummod: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
- Iscourse: {'precision': 0.753731343283582, 'recall': 0.6352201257861635, 'f1': 0.6894197952218429, 'number': 159}
- Islocated: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5}
- Ixed: {'precision': 0.75, 'recall': 0.2608695652173913, 'f1': 0.3870967741935483, 'number': 23}
- Lat:abs: {'precision': 1.0, 'recall': 0.5, 'f1': 0.6666666666666666, 'number': 2}
- Lat:foreign: {'precision': 0.625, 'recall': 0.25, 'f1': 0.35714285714285715, 'number': 20}
- Lat:name: {'precision': 0.631578947368421, 'recall': 0.43636363636363634, 'f1': 0.5161290322580645, 'number': 55}
- Lat:range: {'precision': 0.75, 'recall': 0.5, 'f1': 0.6, 'number': 12}
- Lat:repeat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
- Lat:title: {'precision': 0.616, 'recall': 0.47530864197530864, 'f1': 0.5365853658536586, 'number': 162}
- Mod: {'precision': 0.7972646822204345, 'recall': 0.7155234657039711, 'f1': 0.7541856925418569, 'number': 1385}
- Obj: {'precision': 0.4090909090909091, 'recall': 0.6, 'f1': 0.4864864864864865, 'number': 15}
- Ocative: {'precision': 0.25, 'recall': 1.0, 'f1': 0.4, 'number': 1}
- Oeswith: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Ompound: {'precision': 0.6764705882352942, 'recall': 0.3898305084745763, 'f1': 0.49462365591397844, 'number': 59}
- Onj: {'precision': 0.7439024390243902, 'recall': 0.5831739961759083, 'f1': 0.6538049303322616, 'number': 523}
- Oot: {'precision': 0.9379310344827586, 'recall': 0.9066666666666666, 'f1': 0.9220338983050848, 'number': 600}
- Op: {'precision': 0.7592592592592593, 'recall': 0.7454545454545455, 'f1': 0.7522935779816514, 'number': 55}
- Ppos: {'precision': 0.4262295081967213, 'recall': 0.30952380952380953, 'f1': 0.3586206896551724, 'number': 84}
- Rphan: {'precision': 0.6, 'recall': 0.23076923076923078, 'f1': 0.33333333333333337, 'number': 13}
- Subj: {'precision': 0.8660084626234132, 'recall': 0.8143236074270557, 'f1': 0.8393711551606288, 'number': 754}
- Ummod: {'precision': 0.6153846153846154, 'recall': 0.6, 'f1': 0.6075949367088608, 'number': 40}
- Ummod:gov: {'precision': 0.7352941176470589, 'recall': 0.625, 'f1': 0.6756756756756757, 'number': 40}
- Unct: {'precision': 0.8604790419161676, 'recall': 0.7418688693856479, 'f1': 0.7967840310507347, 'number': 1937}
- Ux: {'precision': 0.6875, 'recall': 0.6111111111111112, 'f1': 0.6470588235294118, 'number': 18}
- Xpl: {'precision': 0.8333333333333334, 'recall': 0.7142857142857143, 'f1': 0.7692307692307692, 'number': 7}
- Overall Precision: 0.8253
- Overall Recall: 0.7232
- Overall F1: 0.7709
- Overall Accuracy: 0.8090

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results



### Framework versions

- Transformers 4.39.3
- Pytorch 1.11.0a0+17540c5
- Datasets 2.21.0
- Tokenizers 0.15.2