new_camembert_jb – AI Model by bjubert | AlphaNeural AI

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bjubert/
new_camembert_jb

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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new_camembert_jb

This model is a fine-tuned version of Jean-Baptiste/camembert-ner on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0752
Overall Precision: 0.8202
Overall Recall: 0.8595
Overall F1: 0.8394
Overall Accuracy: 0.9814
Er F1: 0.8430
Oc F1: 0.8418
Umanprod F1: 0.6933

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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Overall Precision	Overall Recall	Overall F1	Overall Accuracy	Er F1	Oc F1	Umanprod F1
0.2682	1.0	613	0.0813	0.7550	0.8071	0.7802	0.9749	0.7920	0.7709	0.6667
0.0717	2.0	1226	0.0706	0.8139	0.8411	0.8273	0.9808	0.8446	0.8126	0.6857
0.0524	3.0	1839	0.0723	0.8215	0.8567	0.8387	0.9812	0.8462	0.8346	0.7368
0.0372	4.0	2452	0.0752	0.8202	0.8595	0.8394	0.9814	0.8430	0.8418	0.6933

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cpu
Datasets 2.7.1
Tokenizers 0.13.2