closure_system_door_inne-bert-base-uncased

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

• Loss: 1.7907

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: 7
• eval_batch_size: 7
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss
2.7321	1.0	2	2.5801
2.6039	2.0	4	2.0081
2.4556	3.0	6	2.3329
2.3587	4.0	8	2.4156
2.2565	5.0	10	2.0009
2.3489	6.0	12	1.7774
2.2622	7.0	14	2.2064
2.415	8.0	16	1.9671
2.1873	9.0	18	2.0729
2.2377	10.0	20	2.0052
2.352	11.0	22	1.9614
2.2347	12.0	24	2.2437
2.1113	13.0	26	1.7145
2.1939	14.0	28	1.5418
2.0645	15.0	30	2.1882
2.1499	16.0	32	2.0266
2.1432	17.0	34	2.3583
2.0656	18.0	36	2.3147
2.0348	19.0	38	2.2807
2.0502	20.0	40	1.7122

Framework versions

• Transformers 4.18.0
• Pytorch 1.11.0+cu113
• Datasets 2.1.0
• Tokenizers 0.12.1