DNADebertaSentencepiece30k_continuation

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

• Loss: 6.0813

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: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
6.4099	0.41	5000	6.3686
6.4014	0.81	10000	6.3544
6.3816	1.22	15000	6.3338
6.3652	1.62	20000	6.3161
6.3477	2.03	25000	6.2981
6.3305	2.44	30000	6.2851
6.3173	2.84	35000	6.2725
6.306	3.25	40000	6.2559
6.2903	3.66	45000	6.2447
6.2806	4.06	50000	6.2342
6.2654	4.47	55000	6.2213
6.2592	4.87	60000	6.2101
6.2481	5.28	65000	6.2023
6.2394	5.69	70000	6.1929
6.2295	6.09	75000	6.1833
6.219	6.5	80000	6.1800
6.2143	6.91	85000	6.1698
6.2031	7.31	90000	6.1629
6.2036	7.72	95000	6.1523
6.1923	8.12	100000	6.1522
6.1868	8.53	105000	6.1426
6.1827	8.94	110000	6.1356
6.1767	9.34	115000	6.1322
6.1717	9.75	120000	6.1255
6.1649	10.16	125000	6.1221
6.1591	10.56	130000	6.1176
6.1562	10.97	135000	6.1111
6.15	11.37	140000	6.1063
6.1488	11.78	145000	6.1046
6.1449	12.19	150000	6.1023
6.1397	12.59	155000	6.0961
6.135	13.0	160000	6.0938
6.1315	13.41	165000	6.0891
6.1302	13.81	170000	6.0853
6.1295	14.22	175000	6.0838
6.1276	14.62	180000	6.0834

Framework versions

• Transformers 4.19.2
• Pytorch 1.11.0
• Datasets 2.2.2
• Tokenizers 0.12.1