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gechim/metadata-cls-no-gov-8k-vnnic-xml

sourceHugging Facemitupdated 2y agoView on Hugging Face

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metadata-cls-no-gov-8k-vnnic-xml

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

—Loss: 0.3308
—Accuracy: 0.9345
—F1: 0.7072

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
—trainbatchsize: 32
—evalbatchsize: 32
—seed: 42
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	0.5703	150	0.2151	0.9411	0.4945
0.5567	1.1407	300	0.2789	0.9121	0.4579
0.5567	1.7110	450	0.2676	0.9130	0.6930
0.2703	2.2814	600	0.1926	0.9345	0.7071
0.2703	2.8517	750	0.1984	0.9411	0.7390
0.2055	3.4221	900	0.2503	0.9205	0.6689
0.1573	3.9924	1050	0.1895	0.9476	0.7332
0.1573	4.5627	1200	0.3001	0.9130	0.6974
0.1287	5.1331	1350	0.1834	0.9495	0.7302
0.1287	5.7034	1500	0.2586	0.9429	0.7345
0.1022	6.2738	1650	0.3486	0.9261	0.7055
0.1022	6.8441	1800	0.3064	0.9317	0.7053
0.085	7.4144	1950	0.3445	0.9308	0.7086
0.0689	7.9848	2100	0.3342	0.9336	0.7130
0.0689	8.5551	2250	0.3272	0.9345	0.7074
0.0525	9.1255	2400	0.3391	0.9345	0.7030
0.0525	9.6958	2550	0.3308	0.9345	0.7072

Framework versions

—Transformers 4.44.2
—Pytorch 2.1.2
—Datasets 2.20.0
—Tokenizers 0.19.1