vppvgit/Finetuned

BibliBERT

This model is a fine-tuned version of dbmdz/bert-base-italian-xxl-cased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.7784

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: 8
• eval_batch_size: 8
• seed: 0
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss
1.5764	1.0	16528	1.5214
1.4572	2.0	33056	1.4201
1.3787	3.0	49584	1.3728
1.3451	4.0	66112	1.3245
1.3066	5.0	82640	1.2614
1.2447	6.0	99168	1.2333
1.2172	7.0	115696	1.2149
1.2079	8.0	132224	1.1853
1.2167	9.0	148752	1.1586
1.2056	10.0	165280	1.1503
1.1307	11.0	181808	1.1224
1.1689	12.0	198336	1.1074
1.1007	13.0	214864	1.0924
1.0901	14.0	231392	1.0659
1.0667	15.0	247920	1.0650
1.0434	16.0	264448	1.0362
1.0333	17.0	280976	1.0250
1.0342	18.0	297504	1.0198
1.0059	19.0	314032	0.9950
0.9719	20.0	330560	0.9836
0.9863	21.0	347088	0.9873
0.9781	22.0	363616	0.9724
0.9369	23.0	380144	0.9599
0.9578	24.0	396672	0.9557
0.9253	25.0	413200	0.9400
0.9441	26.0	429728	0.9222
0.9138	27.0	446256	0.9140
0.882	28.0	462784	0.9045
0.864	29.0	479312	0.8880
0.8632	30.0	495840	0.9023
0.8342	32.0	528896	0.8740
0.8037	34.0	561952	0.8647
0.8119	37.0	611536	0.8358
0.8011	38.0	628064	0.8252
0.786	39.0	644592	0.8228
0.7697	41.0	677648	0.8138
0.7485	42.0	694176	0.8104
0.7689	43.0	710704	0.8018
0.7401	45.0	743760	0.7957
0.7031	47.0	776816	0.7726
0.7578	48.0	793344	0.7864
0.7298	49.0	809872	0.7775
0.707	50.0	826400	0.7784

Framework versions

• Transformers 4.10.3
• Pytorch 1.9.0+cu102
• Datasets 1.12.1
• Tokenizers 0.10.3