ECHR_test_2

QuentinKemperino/ECHR_test_2

ECHR_test_2 is a text classification model from QuentinKemperino. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as cc-by-sa-4.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
License: cc-by-sa-4.0
Model type: bert
Access: Public
Created: Jun 6, 2022
Updated: Jun 21, 2022
SHA: 2457ef10

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Datasets

lex_glue

Model card

From the Hugging Face model README

ECHR_test_2 Task A

This model is a fine-tuned version of nlpaueb/legal-bert-base-uncased on the lex_glue dataset. It achieves the following results on the evaluation set:

Loss: 0.1998
Macro-f1: 0.5295
Micro-f1: 0.6157

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: 3e-05
train_batch_size: 8
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
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Macro-f1	Micro-f1
0.2142	0.44	500	0.2887	0.2391	0.4263
0.172	0.89	1000	0.2672	0.2908	0.4628
0.1737	1.33	1500	0.2612	0.3657	0.5102
0.1581	1.78	2000	0.2412	0.3958	0.5468
0.1509	2.22	2500	0.2264	0.3950	0.5552
0.1606	2.67	3000	0.2342	0.4006	0.5511
0.1491	3.11	3500	0.2176	0.4558	0.5622
0.1392	3.56	4000	0.2454	0.4128	0.5596
0.15	4.0	4500	0.2113	0.4684	0.5874
0.1461	4.44	5000	0.2179	0.4631	0.5815
0.1457	4.89	5500	0.2151	0.4805	0.5949
0.1443	5.33	6000	0.2155	0.5123	0.5917
0.1279	5.78	6500	0.2131	0.4915	0.5998
0.1377	6.22	7000	0.2244	0.4705	0.5944
0.1242	6.67	7500	0.2150	0.5089	0.5918
0.1222	7.11	8000	0.2045	0.4801	0.5981
0.1372	7.56	8500	0.2074	0.5317	0.5962
0.1289	8.0	9000	0.2035	0.5323	0.6126
0.1295	8.44	9500	0.2058	0.5213	0.6073
0.123	8.89	10000	0.2027	0.5486	0.6135
0.1335	9.33	10500	0.1984	0.5442	0.6249
0.1258	9.78	11000	0.1998	0.5295	0.6157

Framework versions

Transformers 4.19.2
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1

Task: Text Classification
Library: transformers
Type: bert
License: cc-by-sa-4.0
Created: Jun 6, 2022
Updated: Jun 21, 2022