distilbert-base-uncased-finetuned-yahd

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

• Loss: 5.7685
• Accuracy: 0.4010

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 16

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.2439	1.0	9142	2.1898	0.2130
1.9235	2.0	18284	2.1045	0.2372
1.5915	3.0	27426	2.1380	0.2550
1.3262	4.0	36568	2.2544	0.2758
1.0529	5.0	45710	2.5662	0.2955
0.8495	6.0	54852	2.8731	0.3078
0.6779	7.0	63994	3.1980	0.3218
0.5546	8.0	73136	3.6289	0.3380
0.4738	9.0	82278	3.9732	0.3448
0.412	10.0	91420	4.2945	0.3565
0.3961	11.0	100562	4.6127	0.3772
0.3292	12.0	109704	4.9586	0.3805
0.318	13.0	118846	5.2615	0.3887
0.2936	14.0	127988	5.4567	0.3931
0.2671	15.0	137130	5.6902	0.3965
0.2301	16.0	146272	5.7685	0.4010

Framework versions

• Transformers 4.12.3
• Pytorch 1.9.0+cu102
• Datasets 1.15.1
• Tokenizers 0.10.3