DNADebertaSentencepiece30k

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

• Loss: 6.3257

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
7.9373	0.41	5000	7.8263
7.8005	0.81	10000	7.7871
7.7704	1.22	15000	7.7630
7.7477	1.62	20000	7.6857
7.6058	2.03	25000	7.5543
7.5281	2.44	30000	7.4839
7.4487	2.84	35000	7.3801
7.3368	3.25	40000	7.2603
7.1923	3.66	45000	7.0365
6.9858	4.06	50000	6.8793
6.8639	4.47	55000	6.7839
6.7877	4.87	60000	6.7176
6.728	5.28	65000	6.6680
6.6826	5.69	70000	6.6258
6.6414	6.09	75000	6.5847
6.6057	6.5	80000	6.5571
6.5794	6.91	85000	6.5279
6.5525	7.31	90000	6.5059
6.5354	7.72	95000	6.4816
6.5125	8.12	100000	6.4674
6.4958	8.53	105000	6.4486
6.4817	8.94	110000	6.4317
6.4674	9.34	115000	6.4195
6.4549	9.75	120000	6.4072
6.4409	10.16	125000	6.3945
6.4302	10.56	130000	6.3861
6.4214	10.97	135000	6.3755
6.4118	11.37	140000	6.3659
6.4058	11.78	145000	6.3604
6.3985	12.19	150000	6.3560
6.3899	12.59	155000	6.3473
6.3837	13.0	160000	6.3417
6.3782	13.41	165000	6.3361
6.3753	13.81	170000	6.3309
6.3733	14.22	175000	6.3285
6.3706	14.62	180000	6.3277

Framework versions

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