deberta-v3-large__sst2__train-16-9

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: 1.2598
• Accuracy: 0.7809

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6887	1.0	7	0.7452	0.2857
0.6889	2.0	14	0.7988	0.2857
0.6501	3.0	21	0.8987	0.2857
0.4286	4.0	28	0.9186	0.4286
0.3591	5.0	35	0.5566	0.7143
0.0339	6.0	42	1.1130	0.5714
0.013	7.0	49	1.8296	0.7143
0.0041	8.0	56	1.7069	0.7143
0.0023	9.0	63	1.1942	0.7143
0.0022	10.0	70	0.6054	0.7143
0.0011	11.0	77	0.3872	0.7143
0.0006	12.0	84	0.3217	0.7143
0.0005	13.0	91	0.2879	0.8571
0.0005	14.0	98	0.2640	0.8571
0.0004	15.0	105	0.2531	0.8571
0.0003	16.0	112	0.2384	0.8571
0.0004	17.0	119	0.2338	0.8571
0.0003	18.0	126	0.2314	0.8571
0.0003	19.0	133	0.2276	0.8571
0.0003	20.0	140	0.2172	0.8571
0.0003	21.0	147	0.2069	0.8571
0.0002	22.0	154	0.2018	0.8571
0.0002	23.0	161	0.2005	0.8571
0.0002	24.0	168	0.1985	0.8571
0.0002	25.0	175	0.1985	1.0
0.0002	26.0	182	0.1955	1.0
0.0002	27.0	189	0.1967	1.0
0.0002	28.0	196	0.1918	1.0
0.0002	29.0	203	0.1888	1.0
0.0002	30.0	210	0.1864	1.0
0.0002	31.0	217	0.1870	1.0
0.0002	32.0	224	0.1892	1.0
0.0002	33.0	231	0.1917	1.0
0.0002	34.0	238	0.1869	1.0
0.0002	35.0	245	0.1812	1.0
0.0001	36.0	252	0.1777	1.0
0.0002	37.0	259	0.1798	1.0
0.0002	38.0	266	0.1824	0.8571
0.0002	39.0	273	0.1846	0.8571
0.0002	40.0	280	0.1839	0.8571
0.0001	41.0	287	0.1826	0.8571
0.0001	42.0	294	0.1779	0.8571
0.0002	43.0	301	0.1762	0.8571
0.0001	44.0	308	0.1742	1.0
0.0002	45.0	315	0.1708	1.0
0.0001	46.0	322	0.1702	1.0
0.0001	47.0	329	0.1699	1.0
0.0001	48.0	336	0.1695	1.0
0.0001	49.0	343	0.1683	1.0
0.0001	50.0	350	0.1681	1.0

Framework versions

• Transformers 4.15.0
• Pytorch 1.10.2+cu102
• Datasets 1.18.2
• Tokenizers 0.10.3