DNADebertaSentencepiece30k_continuation_continuation

This model is a fine-tuned version of Vlasta/DNADebertaSentencepiece30k_continuation on the None dataset. It achieves the following results on the evaluation set:

• Loss: 5.9867

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
6.1786	0.41	5000	6.1475
6.1856	0.81	10000	6.1490
6.1769	1.22	15000	6.1370
6.1714	1.62	20000	6.1330
6.1633	2.03	25000	6.1221
6.1548	2.44	30000	6.1180
6.1495	2.84	35000	6.1141
6.1453	3.25	40000	6.1026
6.1362	3.66	45000	6.0984
6.1325	4.06	50000	6.0961
6.1227	4.47	55000	6.0874
6.1215	4.87	60000	6.0806
6.1149	5.28	65000	6.0779
6.1099	5.69	70000	6.0701
6.104	6.09	75000	6.0633
6.0963	6.5	80000	6.0628
6.095	6.91	85000	6.0572
6.0858	7.31	90000	6.0525
6.0895	7.72	95000	6.0430
6.0804	8.12	100000	6.0437
6.0767	8.53	105000	6.0371
6.0748	8.94	110000	6.0312
6.0702	9.34	115000	6.0293
6.0668	9.75	120000	6.0242
6.0615	10.16	125000	6.0213
6.0568	10.56	130000	6.0183
6.0552	10.97	135000	6.0125
6.0496	11.37	140000	6.0087
6.0493	11.78	145000	6.0084
6.0466	12.19	150000	6.0060
6.042	12.59	155000	6.0008
6.0375	13.0	160000	5.9986
6.0345	13.41	165000	5.9940
6.0336	13.81	170000	5.9905
6.0334	14.22	175000	5.9891
6.0313	14.62	180000	5.9887

Framework versions

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