roberta-tiny-8l-10M

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 7.3389
• Accuracy: 0.0516

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: 0.0004
• train_batch_size: 16
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 32
• total_train_batch_size: 512
• optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 50
• num_epochs: 100.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
7.8102	1.04	50	7.3747	0.0514
7.805	2.08	100	7.3699	0.0517
7.7907	3.12	150	7.3595	0.0517
7.7838	4.16	200	7.3617	0.0514
7.7706	5.21	250	7.3586	0.0514
7.2933	6.25	300	7.3566	0.0513
7.2932	7.29	350	7.3527	0.0516
7.2986	8.33	400	7.3561	0.0516
7.289	9.37	450	7.3495	0.0515
7.2879	10.41	500	7.3455	0.0514
7.276	11.45	550	7.3477	0.0513
7.3072	12.49	600	7.3446	0.0516
7.2978	13.53	650	7.3463	0.0514
7.2857	14.58	700	7.3426	0.0515
7.2868	15.62	750	7.3438	0.0515
7.2973	16.66	800	7.3442	0.0517
7.2988	17.7	850	7.3437	0.0512

Framework versions

• Transformers 4.24.0
• Pytorch 1.11.0+cu113
• Datasets 2.6.1
• Tokenizers 0.12.1