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izaitova/
robbert-2023-dutch-large_ner

Name: robbert-2023-dutch-large_ner
Availability: InStock

safetensors

roberta

generated_from_trainer

DTAI-KULeuven/robbert-2023-dutch-large

finetune

mit

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robbert-2023-dutch-large_ner

This model is a fine-tuned version of DTAI-KULeuven/robbert-2023-dutch-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3927
Precision: 0.9137
Recall: 0.9190
F1: 0.9162
Accuracy: 0.9515

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

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	438	0.3076	0.8616	0.8592	0.8581	0.9133
0.4231	2.0	876	0.2583	0.9068	0.8795	0.8919	0.9338
0.2222	3.0	1314	0.2809	0.8821	0.8940	0.8864	0.9331
0.1519	4.0	1752	0.2549	0.9142	0.9207	0.9169	0.9505
0.1094	5.0	2190	0.2487	0.9105	0.9145	0.9121	0.9482
0.0731	6.0	2628	0.3406	0.9094	0.9108	0.9097	0.9473
0.0445	7.0	3066	0.3137	0.9118	0.9164	0.9139	0.9498
0.0251	8.0	3504	0.3178	0.9166	0.9209	0.9186	0.9526
0.0251	9.0	3942	0.3886	0.9118	0.9170	0.9143	0.9504
0.0129	10.0	4380	0.3927	0.9137	0.9190	0.9162	0.9515

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

izaitova/robbert-2023-dutch-large_ner

robbert-2023-dutch-large_ner

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

izaitova/
robbert-2023-dutch-large_ner