bert_large_yc_recipe_30

This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0000

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: 8
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	121	0.0026
No log	2.0	242	0.0006
No log	3.0	363	0.0001
No log	4.0	484	0.0000
0.057	5.0	605	0.0000
0.057	6.0	726	0.0000
0.057	7.0	847	0.0000
0.057	8.0	968	0.0000
0.0002	9.0	1089	0.0001
0.0002	10.0	1210	0.0001
0.0002	11.0	1331	0.0002
0.0002	12.0	1452	0.0001
0.0002	13.0	1573	0.0001
0.0002	14.0	1694	0.0001
0.0002	15.0	1815	0.0001
0.0002	16.0	1936	0.0001
0.0	17.0	2057	0.0001
0.0	18.0	2178	0.0001
0.0	19.0	2299	0.0001
0.0	20.0	2420	0.0001
0.0	21.0	2541	0.0001
0.0	22.0	2662	0.0001
0.0	23.0	2783	0.0001
0.0	24.0	2904	0.0001
0.0	25.0	3025	0.0000
0.0	26.0	3146	0.0000
0.0	27.0	3267	0.0000
0.0	28.0	3388	0.0000
0.0	29.0	3509	0.0000
0.0	30.0	3630	0.0000

Framework versions

• Transformers 4.21.1
• Pytorch 1.11.0a0+17540c5
• Datasets 2.4.0
• Tokenizers 0.12.1