fine_tuned_XLMROBERTA_cs_wikann

stulcrad/fine_tuned_XLMROBERTA_cs_wikann

fine_tuned_XLMROBERTA_cs_wikann is a token classification model from stulcrad. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.

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

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At a glance

Task: Token Classification
Library: transformers
License: mit
Model type: xlm-roberta
Access: Public
Created: Jan 16, 2024
Updated: Feb 27, 2024
SHA: a54ffc6c

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Base models

FacebookAI/xlm-roberta-large

Datasets

wikiann

Model card

From the Hugging Face model README

fine_tuned_XLMROBERTA_cs_wikann

This model is a fine-tuned version of FacebookAI/xlm-roberta-large on a czech wikiann dataset. It achieves the following results on the evaluation set:

Loss: 0.1543
Precision: 0.9203
Recall: 0.9342
F1: 0.9272
Accuracy: 0.9732

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.51	0.27	500	0.1995	0.7873	0.8274	0.8069	0.9435
0.2164	0.53	1000	0.2216	0.7743	0.8430	0.8072	0.9407
0.1963	0.8	1500	0.1673	0.8465	0.8849	0.8653	0.9534
0.1478	1.07	2000	0.1612	0.8850	0.9	0.8925	0.9629
0.1316	1.33	2500	0.1508	0.8765	0.9081	0.8920	0.9615
0.1156	1.6	3000	0.1561	0.9028	0.9081	0.9054	0.9656
0.1069	1.87	3500	0.1544	0.9009	0.9091	0.9050	0.9651
0.0925	2.13	4000	0.1724	0.9008	0.9216	0.9111	0.9662
0.0791	2.4	4500	0.1385	0.9096	0.9201	0.9148	0.9705
0.0739	2.67	5000	0.1309	0.9130	0.9254	0.9192	0.9701
0.0732	2.93	5500	0.1593	0.9035	0.9190	0.9112	0.9679
0.0538	3.2	6000	0.1550	0.9193	0.9309	0.9251	0.9722
0.0529	3.47	6500	0.1451	0.9112	0.9330	0.9220	0.9710
0.0521	3.73	7000	0.1510	0.9185	0.9323	0.9253	0.9721
0.0526	4.0	7500	0.1378	0.9173	0.9325	0.9249	0.9727
0.0377	4.27	8000	0.1501	0.9164	0.9344	0.9253	0.9728
0.0382	4.53	8500	0.1541	0.9213	0.9352	0.9282	0.9729
0.0358	4.8	9000	0.1543	0.9203	0.9342	0.9272	0.9732

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.16.1
Tokenizers 0.15.0

Task: Token Classification
Library: transformers
Type: xlm-roberta
License: mit
Created: Jan 16, 2024
Updated: Feb 27, 2024