DNADebertaSentencepiece30k_continuation_continuation_continuation

This model is a fine-tuned version of Vlasta/DNADebertaSentencepiece30k_continuation_continuation on the None dataset. It achieves the following results on the evaluation set:

• Loss: 5.9319

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
6.0844	0.41	5000	6.0623
6.0962	0.81	10000	6.0659
6.0903	1.22	15000	6.0566
6.0874	1.62	20000	6.0550
6.082	2.03	25000	6.0485
6.0756	2.44	30000	6.0446
6.0722	2.84	35000	6.0429
6.0698	3.25	40000	6.0317
6.0627	3.66	45000	6.0297
6.0606	4.06	50000	6.0301
6.0521	4.47	55000	6.0224
6.0526	4.87	60000	6.0159
6.0473	5.28	65000	6.0140
6.0435	5.69	70000	6.0076
6.039	6.09	75000	6.0022
6.032	6.5	80000	6.0037
6.0319	6.91	85000	5.9979
6.0232	7.31	90000	5.9937
6.0279	7.72	95000	5.9844
6.0198	8.12	100000	5.9854
6.0165	8.53	105000	5.9796
6.0153	8.94	110000	5.9741
6.0111	9.34	115000	5.9722
6.0082	9.75	120000	5.9679
6.0035	10.16	125000	5.9654
5.999	10.56	130000	5.9624
5.998	10.97	135000	5.9572
5.9926	11.37	140000	5.9535
5.9927	11.78	145000	5.9533
5.9903	12.19	150000	5.9517
5.986	12.59	155000	5.9459
5.9816	13.0	160000	5.9439
5.9786	13.41	165000	5.9390
5.9781	13.81	170000	5.9357
5.9779	14.22	175000	5.9346
5.9756	14.62	180000	5.9339

Framework versions

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