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domenicrosati/deberta-v3-large-survey-cross_passage_consistency-rater-gpt4

sourceHugging Facemitupdated 3y agoView on Hugging Face

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deberta-v3-large-survey-crosspassageconsistency-rater-gpt4

This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:

—Loss: 0.4075
—Krippendorff: 0.7501
—Spearman: 0.8372
—Absolute Agreement: 0.8907
—Agreement Within One: 0.9799

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: 6e-06
—trainbatchsize: 16
—evalbatchsize: 16
—seed: 42
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—lrschedulerwarmup_steps: 1000
—num_epochs: 20
—mixedprecisiontraining: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Krippendorff	Spearman	Absolute Agreement	Agreement Within One
No log	1.0	50	2.0452	0.0001	nan	0.0694	0.7778
No log	2.0	100	2.0337	0.0175	0.0377	0.0694	0.7778
No log	3.0	150	2.0273	-0.0372	-0.0377	0.0972	0.7778
No log	4.0	200	2.0939	-0.1244	-0.1615	0.125	0.7083
No log	5.0	250	2.1835	-0.1887	0.2306	0.3194	0.6667
No log	6.0	300	2.1351	-0.2704	nan	0.3194	0.6667
No log	7.0	350	2.2556	-0.2704	nan	0.3194	0.6667
No log	8.0	400	2.2676	-0.2704	nan	0.3194	0.6667
No log	9.0	450	2.3103	-0.2704	nan	0.3194	0.6667
1.3588	10.0	500	2.2637	-0.2704	nan	0.3194	0.6667
1.3588	11.0	550	2.3671	-0.2354	-0.1828	0.25	0.6806
1.3588	12.0	600	2.1781	-0.2919	-0.2073	0.2917	0.6667
1.3588	13.0	650	2.1614	-0.1676	0.0113	0.2917	0.6806
1.3588	14.0	700	2.4461	-0.1539	-0.0635	0.2917	0.6806
1.3588	15.0	750	2.4148	-0.0466	0.0219	0.3056	0.6944
1.3588	16.0	800	2.4528	-0.0885	-0.0518	0.2361	0.6806
1.3588	17.0	850	2.4096	-0.0964	0.1186	0.3194	0.6806
1.3588	18.0	900	2.3058	0.1768	0.2017	0.3056	0.7639
1.3588	19.0	950	2.5967	-0.1308	-0.0542	0.3056	0.6944
0.6327	20.0	1000	3.1201	-0.1148	0.0260	0.3194	0.6806

Framework versions

—Transformers 4.26.0
—Pytorch 1.13.1
—Datasets 2.10.1
—Tokenizers 0.12.1